ナレッジグラフ市場 – 2030年までの世界予測

Report Overview

The Knowledge Graph market is estimated at USD 1,068.4 million in 2024 to USD 6,938.4 million by 2030, at a Compound Annual Growth Rate (CAGR) of 36.6%.

ナレッジグラフ市場は、36.6%の年間平均成長率(CAGR)で、2024年に10億6,840万米ドルから2030年までに69億3,840万米ドルに達すると推定されています。

The construction of intelligent knowledge graphs through AI is expected to change how organizations deal with large datasets. The effort of human intervention is drastically reduced when it comes to identifying and extricating relationships between different data points. The automation includes the processes carried out by most types of AI-driven tools such as natural language processing (NLP), machine learning algorithms, etc., to automatically interpret, unstructured or structured data, identify relevant patterns, and correlate such relevant information. This automation speeds up the construction of the graphs and at the same time increases accuracy, ensuring that the relationships represented in it are as relevant and up to date as possible to an end user.

AI によるインテリジェントなナレッジ グラフの構築により、組織が大規模なデータセットを扱う方法が変わると予想されます。異なるデータポイント間の関係を特定して抽出する場合、人的介入の労力が大幅に軽減されます。自動化には、自然言語処理 (NLP) や機械学習アルゴリズムなど、ほとんどのタイプの AI 駆動ツールによって実行されるプロセスが含まれており、非構造化データまたは構造化データを自動的に解釈し、関連するパターンを特定し、関連情報を関連付けます。この自動化により、グラフの構築が高速化されると同時に精度が向上し、グラフ内で表される関係がエンド ユーザーにとって可能な限り関連性があり、最新のものになることが保証されます。

“By solution, Graph Database Engine segment to hold the largest market size during the forecast period.”

Graph Database Engine is a specialized type of database, designed specifically for the efficient storage, management and retrieval of graph data entities (nodes) related by graph relationships (edges). Graph databases do not organize data in tables as in traditional relational systems, but rather as relationships, making them useful in application scenarios where data relationships are paramount, such as social networks, recommendation engines, and fraud detection. It allows high-speed querying and traversing complex and heavily linked datasets, thus enables a more natural, intuitive, and flexible mechanism of data querying. It further supports graph-specific query languages such as SPARQL and Cypher, which are optimized for querying relationships, thus affording better performance and scalability for graph applications.

“The services segment to register the fastest growth rate during the forecast period.”

Knowledge graph services encompass professional and managed services to an organization for deploying, enhancing, and maintaining knowledge graph solutions. Professional services consist of consulting on the design and development of a strategy, integration of the data, and the creation of a custom-built knowledge graph relevant to a business. On the other hand, managed services offer support maintenance, and monitoring of the knowledge graph platform for performance, scalability, and security. These services, in their own way, assist clients in sourcing knowledge graphs to their advantage in terms of getting better data, decision intelligence, and AI, and without the burden of their internal management, which is a resource-intensive and cumbersome process.

“Asia Pacific to witness the highest market growth rate during the forecast period.”

In Asia Pacific, the landscape is characterized by initiatives and innovations that try to help adopt and apply graph technologies across the region. In 2021, Neo4j launched Graphs4APAC initiative, which provides free training, materials, and tools to professionals across Asia Pacific to develop and improve their knowledge and skills in graph technology. This open-source initiative encourages collaborative and local adaptation, and has been successfully implemented in, Indonesia and Singapore. Fujitsu, also, strives to expand the frameworks of knowledge graphs fed by artificial intelligence in the Generative AI Accelerator Challenge (GENIAC) program that focuses on producing dedicated large language models (LLMs) that generate knowledge graphs and allow for inferring such graphs. These are emerging indicators that are significant in portraying how much the region has begun to pay attention to applying knowledge graphs across innovative platforms and data-driven solutions.

In-depth interviews have been conducted with chief executive officers (CEOs), Directors, and other executives from various key organizations operating in the Knowledge Graph market.

• By Company Type: Tier 1 – 40%, Tier 2 – 35%, and Tier 3 – 25%
• By Designation: C-level –40%, D-level – 35%, and Others – 25%
• By Region: North America – 35%, Europe – 40%, Asia Pacific – 20, RoW-5%

The major players in the Knowledge Graph market include IBM Corporation (US), Oracle (US), Microsoft Corporation (US), AWS (US), Neo4j (US), Progress Software (US), TigerGraph (US), Stardog (US), Franz Inc (US), Ontotext (Bulgaria), Openlink Software (US), Graphwise (US), Altair (US), Bitnine ( South Korea) ArangoDB (US),  Fluree (US), Memgraph (UK), Datavid (UK), and SAP (Germany), GraphBase (Australia), Metaphacts (Germany), Relational AI (US), Wisecube (US), Smabbler (Poland), Onlim (Austria), Graphaware (UK), Diffbot (US), Eccenca (Germany), Conversight (US), , Semantic Web Company (Austria), ESRI (US). These players have adopted various growth strategies, such as partnerships, agreements and collaborations, new product launches, enhancements, and acquisitions to expand their Knowledge Graph market footprint.

Research Coverage

The market study covers the Knowledge Graph market size across different segments. It aims at estimating the market size and the growth potential across various segments, including by offering (solutions (enterprise knowledge graph platform, graph database engine, knowledge management toolset), services ( professional services, managed services), by model type (Resource Description Framework (RDF) Triple Stores, Labeled Property Graph (LPG)), by applications (data governance and master data management, data analytics and business intelligence, knowledge and content management , virtual assistants, self-service data and digital asset discovery, product and configuration management, infrastructure and asset management,  process optimization and resource management, risk management, compliance, regulatory reporting, market and customer intelligence, sales optimization, other applications), by vertical (Banking, Financial Services, and Insurance (BFSI), retail and eCommerce, healthcare, life sciences, and pharmaceuticals telecom and technology, government, manufacturing and automotive, media & entertainment, energy, utilities and infrastructure, travel and hospitality, transportation and logistics, other vertical), and Region (North America, Europe, Asia Pacific, Middle East & Africa, and Latin America). The study includes an in-depth competitive analysis of the leading market players, their company profiles, key observations related to product and business offerings, recent developments, and market strategies.

Key Benefits of Buying the Report

The report will help the market leaders/new entrants with information on the closest approximations of the global Knowledge Graph market’s revenue numbers and subsegments. This report will help stakeholders understand the competitive landscape and gain more insights to position their businesses better and plan suitable go-to-market strategies. Moreover, the report will provide insights for stakeholders to understand the market’s pulse and provide them with information on key market drivers, restraints, challenges, and opportunities.

The report provides insights on the following pointers:

Analysis of key drivers (rising demand for AI/generative AI solutions, rapid growth in data volume and complexity, growing demand for semantic search), restraints (data quality and Integration challenges, scalability Issues) opportunities (data unification and rapid proliferation of knowledge graphs, increasing adoption in healthcare and life sciences), and challenges (lack of expertise and awareness, standardization and interoperability) influencing the growth of the Knowledge Graph market.

• Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the Knowledge Graph market.
• Market Development: The report provides comprehensive information about lucrative markets and analyses the Knowledge Graph market across various regions.
• Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the Knowledge Graph market.

Competitive Assessment: In-depth assessment of market shares, growth strategies and service offerings of leading include include IBM Corporation (US), Oracle (US), Microsoft Corporation (US), AWS (US), Neo4j (US), Progress Software (US), TigerGraph (US), Stardog (US), Franz Inc (US), Ontotext (Bulgaria), Openlink Software (US), Graphwise (US), Altair (US), Bitnine ( South Korea) ArangoDB (US),  Fluree (US), Memgraph (UK), GraphBase (Australia), Metaphacts (Germany), Relational AI (US), Wisecube (US), Smabbler (Poland), Onlim (Austria), Graphaware (UK), Diffbot (US), Eccenca (Germany), Conversight (US), , Semantic Web Company (Austria), ESRI (US), Datavid (UK), and SAP (Germany).

Table of Contents

1               INTRODUCTION              40

1.1           STUDY OBJECTIVES       40

1.2           MARKET DEFINITION   40

1.2.1        INCLUSIONS AND EXCLUSIONS 41

1.3           STUDY SCOPE   42

1.3.1        MARKET SEGMENTATION           42

1.3.2        YEARS CONSIDERED      43

1.4           CURRENCY CONSIDERED            43

1.5           STAKEHOLDERS               44

1.6           SUMMARY OF CHANGES               44

2               RESEARCH METHODOLOGY       45

2.1           RESEARCH DATA              45

2.1.1        SECONDARY DATA          46

2.1.1.1    Key data from secondary sources       46

2.1.2        PRIMARY DATA 47

2.1.2.1    Primary interviews with experts         47

2.1.2.2    Breakdown of primary interviews      47

2.1.2.3    Key insights from industry experts    48

2.2           MARKET SIZE ESTIMATION         48

2.2.1        TOP-DOWN APPROACH                48

2.2.1.1    Supply-side analysis             49

2.2.2        BOTTOM-UP APPROACH              50

2.2.2.1    Demand-side analysis          50

2.3           DATA TRIANGULATION                52

2.4           RESEARCH ASSUMPTIONS           53

2.5           RESEARCH LIMITATIONS             54

2.6           RISK ASSESSMENT           54

3               EXECUTIVE SUMMARY  55

4               PREMIUM INSIGHTS       58

4.1           ATTRACTIVE OPPORTUNITIES FOR KEY PLAYERS IN KNOWLEDGE GRAPH MARKET  58

4.2           KNOWLEDGE GRAPH MARKET, BY OFFERING    58

4.3           KNOWLEDGE GRAPH MARKET, BY SERVICE        59

4.4           KNOWLEDGE GRAPH MARKET, BY MODEL TYPE                 59

4.5           KNOWLEDGE GRAPH MARKET, BY APPLICATION                 60

4.6           KNOWLEDGE GRAPH MARKET, BY VERTICAL     60

4.7           NORTH AMERICA: KNOWLEDGE GRAPH MARKET, SOLUTIONS AND SERVICES         61

5               MARKET OVERVIEW AND INDUSTRY TRENDS    62

5.1           INTRODUCTION              62

5.2           MARKET DYNAMICS       62

5.2.1        DRIVERS               63

5.2.1.1    Rising demand for AI/generative AI solutions 63

5.2.1.2    Rapid growth in data volume and complexity  63

5.2.1.3    Growing demand for semantic search               63

5.2.2        RESTRAINTS      63

5.2.2.1    Data quality and integration challenges            63

5.2.2.2    Navigation of saturated data management tool landscape                 64

5.2.2.3    Scalability issues   64

5.2.3        OPPORTUNITIES              64

5.2.3.1    Leveraging LLMs to reduce knowledge graph construction costs                 64

5.2.3.2    Data unification and rapid proliferation of knowledge graphs                 65

5.2.3.3    Increasing adoption in healthcare and life sciences to revolutionize data management and enhance patient outcomes  65

5.2.4        CHALLENGES    65

5.2.4.1    Lack of expertise and awareness        65

5.2.4.2    Standardization and interoperability 66

5.2.4.3    Difficulty in demonstrating full value of knowledge graphs through single use cases      66

5.3           TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS            66

5.4           PRICING ANALYSIS          67

5.4.1        PRICE TREND OF KEY PLAYERS, BY SOLUTION  67

5.4.2        INDICATIVE PRICING ANALYSIS OF KEY PLAYERS                 68

5.5           SUPPLY CHAIN ANALYSIS             69

5.6           ECOSYSTEM       71

5.7           TECHNOLOGY ANALYSIS             73

5.7.1        KEY TECHNOLOGIES     73

5.7.1.1    Graph Databases (GDB)    73

5.7.1.2    Semantic web technologies 73

5.7.1.3    Generative AI and Natural Language Processing (NLP)                 73

5.7.1.4    GraphRAG             74

5.7.2        COMPLEMENTARY TECHNOLOGIES       74

5.7.2.1    Artificial Intelligence (AI) and Machine Learning (ML)                 74

5.7.2.2    Big data  74

5.7.2.3    Graph Neural Networks (GNNS)      74

5.7.2.4    Cloud computing  75

5.7.2.5    Vector databases and Full-Text Search Engines (FTS) 75

5.7.2.6    Multi-model databases        75

5.7.3        ADJACENT TECHNOLOGIES       76

5.7.3.1    Digital twin            76

5.7.3.2    Internet of Things (IoT)     76

5.7.3.3    Blockchain             76

5.7.3.4    Edge computing   76

5.8           PATENT ANALYSIS          77

5.8.1        METHODOLOGY              77

5.8.1.1    List of major patents            78

5.9           KEY CONFERENCES AND EVENTS, 2024–2025        80

5.10         REGULATORY LANDSCAPE         81

5.10.1      REGULATORY BODIES, GOVERNMENT AGENCIES,

AND OTHER ORGANIZATIONS  81

5.10.2      KEY REGULATIONS         85

5.10.2.1  North America      85

5.10.2.1.1                SCR 17: Artificial Intelligence Bill (California)                 85

5.10.2.1.2                S1103: Artificial Intelligence Automated Decision Bill (Connecticut)        85

5.10.2.1.3                National Artificial Intelligence Initiative Act (NAIIA)                 85

5.10.2.1.4                The Artificial Intelligence and Data Act (AIDA) – Canada   85

5.10.2.2  Europe   86

5.10.2.2.1                The European Union (EU) – Artificial Intelligence Act (AIA)      86

5.10.2.2.2                EU Data Governance Act   86

5.10.2.2.3                General Data Protection Regulation (Europe)                 86

5.10.2.3  Asia Pacific            87

5.10.2.3.1                Interim Administrative Measures for Generative Artificial Intelligence Services (China)             87

5.10.2.3.2                The National AI Strategy (Singapore)               88

5.10.2.3.3                The Hiroshima AI Process Comprehensive Policy Framework (Japan)              88

5.10.2.4  Middle East & Africa            88

5.10.2.4.1                The National Strategy for Artificial Intelligence (UAE)                 88

5.10.2.4.2                The National Artificial Intelligence Strategy (Qatar)                 89

5.10.2.4.3                The AI Ethics Principles and Guidelines (Dubai)                 89

5.10.2.5  Latin America       90

5.10.2.5.1                The Santiago Declaration (Chile)     90

5.10.2.5.2                The Brazilian Artificial Intelligence Strategy (EBIA)                 90

5.11         PORTER’S FIVE FORCES ANALYSIS           91

5.11.1      THREAT OF NEW ENTRANTS      92

5.11.2      THREAT OF SUBSTITUTES          92

5.11.3      BARGAINING POWER OF BUYERS             92

5.11.4      BARGAINING POWER OF SUPPLIERS       92

5.11.5      INTENSITY OF COMPETITIVE RIVALRY 92

5.12         KEY STAKEHOLDERS & BUYING CRITERIA            93

5.12.1      KEY STAKEHOLDERS IN BUYING PROCESS           93

5.12.2      BUYING CRITERIA           93

5.13         BRIEF HISTORY OF KNOWLEDGE GRAPH              94

5.14         STEPS TO BUILD KNOWLEDGE GRAPH 95

5.14.1      DEFINE OBJECTIVES      95

5.14.2      ENGAGE STAKEHOLDERS            95

5.14.3      IDENTIFY KNOWLEDGE DOMAIN             95

5.14.4      GATHER AND ANALYZE DATA   96

5.14.5      CLEAN AND PREPROCESS DATA               96

5.14.6      CREATE SEMANTIC DATA MODEL           96

5.14.7      SCHEMA DEFINITION    96

5.14.8      DATA INTEGRATION     96

5.14.9      HARMONIZATION OF DATA       96

5.14.10   BUILD KNOWLEDGE GRAPH       96

5.14.11   AUGMENT GRAPH           96

5.14.12   TESTING AND VALIDATION       96

5.14.13   MAXIMIZE USABILITY    96

5.14.14   CONTINUOUS MAINTENANCE AND EVOLUTION                 96

5.15         IMPACT OF AI/GENERATIVE AI ON KNOWLEDGE GRAPH MARKET               97

5.15.1      USE CASES OF GENERATIVE KNOWLEDGE GRAPH                 97

5.16         INVESTMENT AND FUNDING SCENARIO               99

5.17         CASE STUDY ANALYSIS 99

5.17.1      TRANSMISSION SYSTEM OPERATOR LEVERAGED ONTOTEXT’S SOLUTIONS TO MODERNIZE ASSET MANAGEMENT 99

5.17.2      BOSTON SCIENTIFIC STREAMLINED MEDICAL SUPPLY CHAIN USING NEO4J’S GRAPH DATA SCIENCE SOLUTION                 100

5.17.3      NATIONAL RETAIL CHAIN FROM UK ENHANCED OPERATIONAL EFFICIENCY USING TIGERGRAPHS’S SOLUTION                 101

5.17.4      SCHNEIDER ELECTRIC USED STARDOG TO LEAD SMART BUILDING TRANSFORMATION  101

5.17.5      MEDIA ORGANIZATION USED PROGRESS SEMAPHORE TO CLASSIFY CONTENT FOR BETTER AUDIENCE ENGAGEMENT                 102

5.17.6      YAHOO7 REPRESENTED CONTENT WITHIN KNOWLEDGE GRAPH WITH ASSISTANCE OF BLAZEGRAPH                 103

5.17.7      DATABASE GROUP HELPED SPRINGERMATERIALS ACCELERATE RESEARCH WITH SEMANTIC SEARCH         103

5.17.8      RFS OPTIMIZED ITS GLOBAL PRODUCT AND INVENTORY MANAGEMENT BY USING ECCENCA’S SOLUTION                 104

6               KNOWLEDGE GRAPH MARKET, BY OFFERING    106

6.1           INTRODUCTION              107

6.1.1        OFFERINGS: KNOWLEDGE GRAPH MARKET DRIVERS                 107

6.2           SOLUTIONS        108

6.2.1        SPIKE IN DEMAND FOR SOPHISTICATED DATA MANAGEMENT AND

ANALYSIS TO DRIVE MARKET    108

6.2.2        ENTERPRISE KNOWLEDGE GRAPH PLATFORM  110

6.2.2.1    Need to improve discovery of data, promote better decision-making, and enable real-time insights using semantic technologies to propel market        110

6.2.3        GRAPH DATABASE ENGINE         111

6.2.3.1    Features like parallel query execution and AI-driven insights in graph database engines to accelerate market growth      111

6.2.4        KNOWLEDGE MANAGEMENT TOOLSET                112

6.2.4.1    Knowledge management toolsets to enhance operational efficiency by enabling seamless access to organizational knowledge                 112

6.3           SERVICES             113

6.3.1        PROFESSIONAL SERVICES            115

6.3.2        MANAGED SERVICES      116

7               KNOWLEDGE GRAPH MARKET, BY MODEL TYPE                 117

7.1           INTRODUCTION              118

7.1.1        MODEL TYPES: KNOWLEDGE GRAPH MARKET DRIVERS                 118

7.2           RESOURCE DESCRIPTION FRAMEWORK (RDF) TRIPLE STORES                 119

7.2.1        RDF-BASED KNOWLEDGE GRAPHS TO FACILITATE APPLICATIONS REQUIRING SEMANTIC INTEROPERABILITY                 119

7.3           LABELED PROPERTY GRAPH (LPG)         120

7.3.1        LOGICAL INFERENCE, KNOWLEDGE DISCOVERY, AND STRUCTURED REPRESENTATION OF DATA TO BOOST MARKET GROWTH             120

8               KNOWLEDGE GRAPH MARKET, BY APPLICATION                 122

8.1           INTRODUCTION              123

8.1.1        APPLICATIONS: KNOWLEDGE GRAPH MARKET DRIVERS               123

8.2           DATA GOVERNANCE AND MASTER DATA MANAGEMENT 125

8.2.1        NEED FOR ENHANCED SEARCH FUNCTIONALITIES TO BOLSTER MARKET GROWTH      125

8.3           DATA ANALYTICS & BUSINESS INTELLIGENCE  126

8.3.1        INTEGRATION OF KNOWLEDGE FROM SEVERAL DISCIPLINES AND OFFERING PERSONALIZED RECOMMENDATIONS TO BOOST MARKET GROWTH     126

8.4           KNOWLEDGE & CONTENT MANAGEMENT          127

8.4.1        WIDESPREAD KNOWLEDGE OF INTRICATE IDEAS THROUGH CROSS-DOMAIN INFORMATION INTEGRATION TO BOOST MARKET               127

8.5           VIRTUAL ASSISTANTS, SELF-SERVICE DATA, AND DIGITAL ASSET DISCOVERY       128

8.5.1        STREAMLINING OF TEAMWORK AND KNOWLEDGE EXCHANGE TO ACCELERATE MARKET GROWTH              128

8.6           PRODUCT & CONFIGURATION MANAGEMENT 129

8.6.1        NEED TO ENSURE ACCURACY AND REDUCES TIME-TO-MARKET ENHANCING CUSTOMER SATISFACTION TO FUEL MARKET GROWTH          129

8.7           INFRASTRUCTURE & ASSET MANAGEMENT        130

8.7.1        INFRASTRUCTURE AND ASSET MANAGEMENT TO REDUCE DOWNTIME AND EXTEND ASSET LIFECYCLES THROUGH INFORMED DECISION-MAKING PROCESSES 130

8.8           PROCESS OPTIMIZATION & RESOURCE MANAGEMENT                 131

8.8.1        NEED FOR REAL-TIME RESOURCE UTILIZATION MONITORING ACROSS DIFFERENT PROJECTS OR DEPARTMENTS TO PROPEL MARKET     131

8.9           RISK MANAGEMENT, COMPLIANCE, AND REGULATORY REPORTING       132

8.9.1        RISK MANAGEMENT, COMPLIANCE, AND REGULATORY REPORTING TO HELP MAP DATA FLOWS, RELATIONSHIPS, AND CONTROLS TO IDENTIFY VULNERABILITIES AND ENSURE COMPLIANCE    132

8.10         MARKET & CUSTOMER INTELLIGENCE AND SALES OPTIMIZATION                133

8.10.1      NEED TO IDENTIFY TRENDS INFORMING TARGETED MARKETING STRATEGIES TO DRIVE MARKET    133

8.11         OTHER APPLICATIONS 134

9               KNOWLEDGE GRAPH MARKET, BY VERTICAL     135

9.1           INTRODUCTION              136

9.1.1        VERTICALS: KNOWLEDGE GRAPH MARKET DRIVERS                 136

9.2           BFSI       138

9.2.1        INCREASING NEED TO MANAGE COMPLEX DATA TO SUPPORT MARKET GROWTH     138

9.2.2        CASE STUDY      139

9.2.2.1    Аnti-money laundering (AML)         139

9.2.2.1.1 Major US Financial Institutions enhanced anti-money laundering capabilities with TigerGraph              139

9.2.2.2    Fraud detection & risk management 140

9.2.2.2.1 BNP Paribas Personal Finance achieved 20% fraud reduction with Neo4j Graph Database                140

9.2.2.3    Identity & access management           140

9.2.2.3.1 Intuit safeguarded data of 100 million customers with Neo4j                 140

9.2.2.4    Risk management 140

9.2.2.4.1 Global bank enhanced trade surveillance for risk management in BFSI       140

9.2.2.5    Data integration & governance           141

9.2.2.5.1 Optimizing data integration and governance for real-time risk management and compliance             141

9.2.2.6    Operational resilience for bank IT systems      141

9.2.2.6.1 Basel Institute on Governance enhanced asset recovery and financial intelligence with knowledge graphs for global financial institutions with Ontotext   141

9.2.2.7    Regulatory compliance        141

9.2.2.7.1 Multinational auditing company enhanced regulatory compliance and operational efficiency with knowledge graphs of Ontotext     141

9.2.2.8    Customer 360° view           142

9.2.2.8.1 Intuit enhanced security and data protection using Neo4j knowledge graph for customer data  142

9.2.2.9    Know Your Customer (KYC) processes            142

9.2.2.9.1 AI-powered knowledge graphs streamlined KYC compliance and adverse media analysis in financial services     142

9.2.2.10  Market analysis and trend detection 143

9.2.2.10.1                Leading investment bank enhanced investment insights through comprehensive company knowledge graph       143

9.2.2.11  Policy impact analysis          143

9.2.2.11.1                Delinian enhanced content production and analysis with semantic publishing platform    143

9.2.2.12  Customer support 143

9.2.2.12.1                Banks and insurance companies improved AI-powered knowledge graphs to revolutionize customer support in BFSI      143

9.2.2.13  Self-service data & digital asset discovery and data integration & governance             144

9.2.2.13.1                HSBC revolutionized data governance with knowledge graphs in BFSI      144

9.3           RETAIL & ECOMMERCE 144

9.3.1        NEED TO OPTIMIZE INVENTORY MANAGEMENT FACILITATED BY KNOWLEDGE GRAPHS TO DRIVE MARKET                 144

9.3.2        CASE STUDY      145

9.3.2.1    Fraud detection in eCommerce          145

9.3.2.1.1 PayPal enhanced fraud detection with knowledge graphs                 145

9.3.2.2    Dynamic pricing optimization            145

9.3.2.2.1 Belgian company revolutionized new product development with food pairing knowledge graph            145

9.3.2.3    Personalized recommendations          146

9.3.2.3.1 Xandr created industry-leading identity graph for personalized advertising with TigerGraph               146

9.3.2.4    Market basket analysis         146

9.3.2.4.1 eCommerce giants boosted retail sales with knowledge graph-powered market basket analysis         146

9.3.2.5    Customer experience enhancement  146

9.3.2.5.1 Retailers improved store operations and increased customer satisfaction using TigerGraph            146

9.3.2.5.2 Edamam enhanced food knowledge and user experience with knowledge graphs 147

9.3.2.6    Social media influence on buying behavior      147

9.3.2.6.1 Leveraging knowledge graphs to track social media influence on buying behavior at Coca-Cola             147

9.3.2.7    Churn prediction & prevention          147

9.3.2.7.1 Reduction of customer churn with knowledge graphs    147

9.3.2.8    Product configuration & recommendation       147

9.3.2.8.1 Leading automotive manufacturer personalized customer experience with knowledge graphs for product configuration       147

9.3.2.9    Customer segmentation & targeting 148

9.3.2.9.1 Xbox enhanced user experience with TigerGraph for better customer insights and loyalty              148

9.3.2.10  Customer 360° view           148

9.3.2.10.1                Technology giant enhanced customer engagement with TigerGraph for personalized experiences         148

9.3.2.11  Review & reputation management     149

9.3.2.11.1                Neo4j managed brand reputation with knowledge graphs at TripAdvisor          149

9.3.2.12  Customer support 149

9.3.2.12.1                Retailer enhanced operations and customer satisfaction with TigerGraph for root cause analysis           149

9.4           HEALTHCARE, LIFE SCIENCES, AND PHARMACEUTICALS       149

9.4.1        NEED TO REVOLUTIONIZE HEALTHCARE PRACTICES TO PROPEL ADOPTION OF KNOWLEDGE GRAPHS           149

9.4.2        CASE STUDY      150

9.4.2.1    Drug discovery & development          150

9.4.2.1.1 Early Drug R&D center accelerated cancer research with Ontotext’s target discovery 150

9.4.2.1.2 Ontotext’s Target Discovery accelerated Alzheimer’s breakthroughs with knowledge graphs              151

9.4.2.2    Clinical trial management   151

9.4.2.2.1 NuMedii streamlined clinical trial management with

AI-powered knowledge graphs with Ontotext 151

9.4.2.3    Medical claim processing    152

9.4.2.3.1 UnitedHealth Group revolutionized medical claim processing with TigerGraph   152

9.4.2.4    Clinical intelligence              152

9.4.2.4.1 Leading US Children’s Hospital gained deeper insights into impact of its faculty research              152

9.4.2.5    Healthcare provider network analysis                152

9.4.2.5.1 Amgen improved quality of healthcare by identifying influencers and referral networks using TigerGraph           152

9.4.2.6    Customer support 153

9.4.2.6.1 Exact Sciences Corporation revolutionized customer support in healthcare with a knowledge graph-powered 360° View              153

9.4.2.7    Patient journey & care pathway analysis           153

9.4.2.7.1 Care-for-Rare Foundation at Dr. von Hauner Children’s Hospital transformed pediatric care pathways with Neo4j’s clinical knowledge graph                 153

9.4.2.8    Self-service data & digital asset discovery         153

9.4.2.8.1 Boehringer Ingelheim accelerating pharmaceutical innovation with Stardog Knowledge Graph         153

9.5           TELECOM & TECHNOLOGY         154

9.5.1        NEED TO OPTIMIZE INTRICATE NETWORK INFRASTRUCTURE AND CUSTOMIZED SERVICE OFFERINGS TO FUEL MARKET GROWTH               154

9.5.2        CASE STUDY      155

9.5.2.1    Network optimization & management               155

9.5.2.1.1 Cyber resilience leader scaled next-generation cybersecurity with TigerGraph to combat evolving threats            155

9.5.2.2    Network security analysis   155

9.5.2.2.1 Multinational cybersecurity and defense company accelerated risk identification in cybersecurity with knowledge graphs with Ontotext                 155

9.5.2.3    Identity & access management           155

9.5.2.3.1 Technology giant improved customer experiences with TigerGraph            155

9.5.2.4    IT asset management           156

9.5.2.4.1 Orange used Thing’in to build digital twin platform      156

9.5.2.5    IoT device management & connectivity            156

9.5.2.5.1 AWS enhanced IoT device management with Amazon Neptune’s scalable graph database solutions      156

9.5.2.6    Metadata enrichment           156

9.5.2.6.1 Cisco utilized Neo4j to enhance and assign metadata to its vast document collection             156

9.5.2.7    Data integration & governance           157

9.5.2.7.1 Dun & Bradstreet enhanced compliance with Neo4j’s graph technology              157

9.5.2.8    Self-service data & digital asset discovery         157

9.5.2.8.1 Telecom provider optimized telecom operations with Neo4j’s self-service data and digital asset discovery     157

9.5.2.9    Service incident management             157

9.5.2.9.1 BT Group revolutionizing telecom inventory management with Neo4j knowledge graph       157

9.6           GOVERNMENT 157

9.6.1        SPEEDY DATA INTEGRATION AND INTEROPERABILITY TO BOOST MARKET GROWTH   157

9.6.2        CASE STUDY      158

9.6.2.1    Government service optimization      158

9.6.2.1.1 LODAC Museum project, initiated by Japan’s National Institute of Informatics (NII), enhanced academic access to cultural heritage data through Linked Open Data 158

9.6.2.2    Legislative & regulatory analysis        159

9.6.2.2.1 Inter-American Development Bank (IDB) enhanced knowledge discovery with knowledge graphs at the IDB   159

9.6.2.3    Crisis management & disaster response planning           159

9.6.2.3.1 Knowledge graphs enhanced crisis response for real-time decision-making   159

9.6.2.4    Environmental impact analysis and ESG          159

9.6.2.4.1 Vienna University of Technology transformed architectural design with ECOLOPES knowledge graph      159

9.6.2.5    Social network analysis for security & law enforcement 160

9.6.2.5.1 Social Network Analysis strengthened security via knowledge graphs    160

9.6.2.6    Policy Impact Analysis         160

9.6.2.6.1 Governments leveraged knowledge graphs for effective policy impact analysis      160

9.6.2.7    Knowledge management     160

9.6.2.7.1 Ellas leveraged Graphdb’s knowledge graphs to bridge gender gaps in STEM leadership    160

9.6.2.8    Data integration & governance           160

9.6.2.8.1 Government agency took digital and print library services to next level partnering with metaphacts and Ontotext               160

9.7           MANUFACTURING & AUTOMOTIVE        161

9.7.1        EASY PREDICTIVE MAINTENANCE AND DECREASE IN DOWNTIME TO SUPPORT MARKET GROWTH    161

9.7.2        CASE STUDY      162

9.7.2.1    Equipment maintenance and predictive maintenance    162

9.7.2.1.1 Ford Motor Company enhanced production efficiency with TigerGraph for predictive maintenance            162

9.7.2.2    Product lifecycle management            162

9.7.2.2.1 Leading European manufacturer of electrical components enhanced product discoverability through semantic knowledge graphs                 162

9.7.2.3    Manufacturing process optimization 163

9.7.2.3.1 Production streamlined efficiency with knowledge graphs                 163

9.7.2.4    Enhance vehicle safety & reliability   163

9.7.2.4.1 Knowledge graphs improved vehicle safety with predictive maintenance          163

9.7.2.5    Optimization of industrial processes 163

9.7.2.5.1 Leading manufacturer of Building Automation Systems (BAS) graphs improved vehicle safety with Ontotext’s GraphDB            163

9.7.2.6    Root cause analysis               164

9.7.2.6.1 Root Cause Analysis uncovered process failures with using knowledge graphs 164

9.7.2.7    Inventory management & demand forecasting                 164

9.7.2.7.1 Knowledge graphs optimized inventory and demand forecasting with knowledge graphs        164

9.7.2.8    Service incident management             164

9.7.2.8.1 Knowledge graphs accelerated service incident resolution with knowledge graphs 164

9.7.2.9    Staff & resource allocation  164

9.7.2.9.1 Knowledge graphs optimized staff and resource allocation with knowledge graphs 164

9.7.2.10  Product configuration & recommendation       165

9.7.2.10.1                Leading Building Automation Systems (BAS) manufacturers used Brick schema to represent BAS components and their complex interactions            165

9.8           MEDIA & ENTERTAINMENT        165

9.8.1        NEED TO IMPROVE CONTENT MANAGEMENT PROCEDURES AND BETTER DATA-DRIVEN DECISIONS TO FOSTER MARKET GROWTH         165

9.8.2        CASE STUDY      166

9.8.2.1    Content recommendation & personalization   166

9.8.2.1.1 Leading television broadcaster streamlined data management and improved search efficiency with knowledge graphs 166

9.8.2.2    Audience segmentation & targeting  166

9.8.2.2.1 KT Corporation enhanced IPTV Content Discovery with semantic search for better audience targeting 166

9.8.2.3    Social media influence analysis          167

9.8.2.3.1 Myntelligence used TigerGraph’s advanced graph analytics to analyze relationships and interactions               167

9.8.2.4    Copyright & licensing management  167

9.8.2.4.1 British Museum and Europeana leveraged knowledge graphs for efficient content management and licensing in cultural heritage 167

9.8.2.5    Self-service data & digital asset discovery         167

9.8.2.5.1 BBC transformed content management with semantic publishing for enhanced user experience              167

9.8.2.6    Content recommendation systems    168

9.8.2.6.1 STM publisher leveraged knowledge platform for enhanced content recommendation    168

9.8.2.7    User engagement analysis   168

9.8.2.7.1 Bulgarian media company leveraged Ontotext’s knowledge graphs for enhanced user engagement and ad targeting                 168

9.8.2.8    Knowledge management     169

9.8.2.8.1 Rappler empowered transparent elections with first Philippine Politics Knowledge Graph  169

9.8.2.8.2 Perfect Memory and Ontotext developed custom data program platform based on knowledge graph solution to streamline data management          169

9.9           ENERGY, UTILITIES, AND INFRASTRUCTURE      169

9.9.1        DEVELOPMENT OF INNOVATIVE TECHNOLOGIES TO DRIVE DEMAND FOR KNOWLEDGE GRAPH SOLUTIONS                 169

9.9.2        CASE STUDY      170

9.9.2.1    Grid management 170

9.9.2.1.1 Transmission Systems Operator (TSO) modernized asset management with knowledge graphs for enhanced grid reliability                 170

9.9.2.2    Energy trading optimization               171

9.9.2.2.1 Global energy and commodities markets information provider gained enhanced operational efficiencies with semantic information extraction               171

9.9.2.3    Renewable energy integration & optimization 171

9.9.2.3.1 State Grid Corporation of China created speedy energy management system with assistance of TigerGraph       171

9.9.2.4    Public infrastructure management    171

9.9.2.4.1 Knowledge graphs enhanced infrastructure management for better decision-making        171

9.9.2.5    Customer engagement & billing        172

9.9.2.5.1 Knowledge graphs streamlined customer engagement and billing                 172

9.9.2.6    Environmental impact analysis & ESG              172

9.9.2.6.1 Improved environmental impact analysis with knowledge graphs for ESG reporting 172

9.9.2.7    Service incident management             172

9.9.2.7.1 Enxchange transformed service incident management in energy with graph-based digital twins            172

9.9.2.8    Staff & resource allocation  172

9.9.2.8.1 Knowledge graphs optimized staff and resource allocation for efficient operations               172

9.9.2.9    Railway asset management 173

9.9.2.9.1 Railway asset management with graph databases enhanced connectivity and efficiency 173

9.10         TRAVEL & HOSPITALITY               173

9.10.1      NEED FOR KNOWLEDGE GRAPHS TO HELP DEVELOP INNOVATIVE TECHNOLOGIES TO DRIVE MARKET           173

9.10.2      CASE STUDY      174

9.10.2.1  Personalized travel recommendations               174

9.10.2.1.1                Travel personalization with knowledge graphs for tailored recommendations  174

9.10.2.2  Dynamic pricing optimization            174

9.10.2.2.1                Marriott International implemented knowledge graph technology for dynamic pricing and revenue optimization            174

9.10.2.3  Customer journey mapping                 174

9.10.2.3.1                Knowledge graphs mapped customer journey for enhanced travel experiences                174

9.10.2.4  Booking & reservation optimization  175

9.10.2.4.1                WestJet Airlines transformed flight scheduling into a seamless, customer-friendly experience with Neo4j       175

9.10.2.5  Customer experience enhancement  175

9.10.2.5.1                Airbnb transformed customer experience with unified data and actionable insights with Neo4j graph database                175

9.10.2.6  Product configuration and recommendation   175

9.10.2.6.1                Knowledge graphs streamlined product configuration and recommendations          175

9.11         TRANSPORTATION & LOGISTICS              176

9.11.1      NEED FOR DEVELOPMENT OF INNOVATIVE TECHNOLOGIES TO BOLSTER MARKET GROWTH            176

9.11.2      CASE STUDY      177

9.11.2.1  Route optimization & fleet management          177

9.11.2.1.1                Transport for London (TfL) optimized route management and incident response with digital twin     177

9.11.2.2  Supply chain visibility          177

9.11.2.2.1                Knowledge graphs enhanced supply chain visibility with real-time insights 177

9.11.2.3  Equipment maintenance & predictive maintenance       177

9.11.2.3.1                Knowledge graphs optimized equipment maintenance with predictive insights via knowledge graphs 177

9.11.2.4  Supply chain management  177

9.11.2.4.1                Knowledge graphs streamlined supply chain management for better coordination 177

9.11.2.5  Vendor & supplier analysis 178

9.11.2.5.1                Vendor and supplier analysis with knowledge graphs for smarter sourcing   178

9.11.2.6  Operational efficiency & decision making        178

9.11.2.6.1                Careem improved operational efficiency through fraud detection                 178

9.12         OTHER VERTICALS         178

10            KNOWLEDGE GRAPH MARKET, BY REGION         180

10.1         INTRODUCTION              181

10.2         NORTH AMERICA             182

10.2.1      NORTH AMERICA: MACROECONOMIC OUTLOOK                 182

10.2.2      US           188

10.2.2.1  Increasing need for structured data analytics and interoperability to drive market      188

10.2.3      CANADA               193

10.2.3.1  Increasing complexity of data and demand for efficient data to propel market        193

10.3         EUROPE               193

10.3.1      EUROPE: MACROECONOMIC OUTLOOK               194

10.3.2      UK          199

10.3.2.1  Increasing complexity of data and demand for advanced data integration solutions to fuel market growth     199

10.3.3      GERMANY           204

10.3.3.1  Focus on Industry 4.0 to drive demand for knowledge graph                 204

10.3.4      FRANCE                204

10.3.4.1  Focus on technological innovation, robust digital infrastructure,

and supportive regulatory environment to foster market growth 204

10.3.5      ITALY    204

10.3.5.1  Increasing adoption of semantic technologies and government commitment to fostering innovation to drive market     204

10.3.6      SPAIN    209

10.3.6.1  Strategic initiatives in AI development sector and implementation of Spain’s 2024 Artificial Intelligence Strategy to accelerate market 209

10.3.7      NORDIC COUNTRIES     210

10.3.7.1  High digital literacy, advanced AI readiness, and robust public-private partnerships to bolster market growth 210

10.3.8      REST OF EUROPE             210

10.4         ASIA PACIFIC     211

10.4.1      ASIA PACIFIC: MACROECONOMIC OUTLOOK     211

10.4.2      CHINA  217

10.4.2.1  Rapid technological advancements, government initiatives,

and strategic focus on integrating AI to boost market    217

10.4.3      JAPAN   222

10.4.3.1  Advancements in robotics and a strong focus on AI technologies under the government’s “Society 5.0” initiative to drive market  222

10.4.4      INDIA    222

10.4.4.1  Focus on promoting advanced technology usage through government initiatives to foster market growth               222

10.4.5      SOUTH KOREA  227

10.4.5.1  Strong focus on developing and enhancing public-private partnerships to drive market               227

10.4.6      AUSTRALIA & NEW ZEALAND     227

10.4.6.1  Strategic collaborations for development in new age technologies to drive market      227

10.4.7      REST OF ASIA PACIFIC   227

10.5         MIDDLE EAST & AFRICA                228

10.5.1      MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK                 228

10.5.2      GCC COUNTRIES              233

10.5.2.1  Increasing investment in AI technologies for development to fuel market growth       233

10.5.2.2  UAE        238

10.5.2.2.1                Rising government support for AI and digital transformation initiatives to foster market growth          238

10.5.2.3  KSA        239

10.5.2.3.1                Government initiatives and investments in digital infrastructure to propel market          239

10.5.2.4  Rest of GCC countries         243

10.5.3      SOUTH AFRICA 243

10.5.3.1  Growing focus on digital transformation and innovation to accelerate market growth    243

10.5.4      REST OF MIDDLE EAST & AFRICA             244

10.6         LATIN AMERICA                244

10.6.1      LATIN AMERICA: MACROECONOMIC OUTLOOK                 244

10.6.2      BRAZIL 250

10.6.2.1  Increasing demand for personalized customer interactions and advancements in AI technologies to propel market         250

10.6.3      MEXICO                254

10.6.3.1  Focus on advancing digital infrastructure to boost market growth                 254

10.6.4      ARGENTINA       255

10.6.4.1  Focus on digital transformation initiatives to drive market                 255

10.6.5      REST OF LATIN AMERICA             255

11            COMPETITIVE LANDSCAPE         256

11.1         INTRODUCTION              256

11.2         KEY PLAYER STRATEGIES/RIGHT TO WIN            256

11.3         REVENUE ANALYSIS       257

11.4         MARKET SHARE ANALYSIS           258

11.5         MARKET RANKING ANALYSIS     259

11.6         COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023                 260

11.6.1      STARS   260

11.6.2      EMERGING LEADERS     260

11.6.3      PERVASIVE PLAYERS      260

11.6.4      PARTICIPANTS 261

11.6.5      COMPANY FOOTPRINT: KEY PLAYERS, 2024         262

11.6.5.1  Company footprint               262

11.6.5.2  Vertical footprint  263

11.6.5.3  Offering footprint 264

11.6.5.4  Regional footprint                 265

11.7         COMPANY EVALUATION MATRIX: START-UPS/SMES, 2024        265

11.7.1      PROGRESSIVE COMPANIES         265

11.7.2      RESPONSIVE COMPANIES            265

11.7.3      DYNAMIC COMPANIES  266

11.7.4      STARTING BLOCKS         266

11.7.5      COMPETITIVE BENCHMARKING: START-UPS/SMES, 2024        267

11.7.5.1  Key start-ups/SMEs             267

11.7.5.2  Competitive benchmarking of key start-ups/SMEs        268

11.8         COMPETITIVE SCENARIOS AND TRENDS              269

11.8.1      PRODUCT LAUNCHES & ENHANCEMENTS           269

11.8.2      DEALS  272

11.9         BRAND/PRODUCT COMPARISON             274

11.10       COMPANY VALUATION AND FINANCIAL METRICS OF KEY KNOWLEDGE GRAPH SOLUTION PROVIDERS           275

12            COMPANY PROFILES      276

12.1         KEY PLAYERS     276

12.1.1      NEO4J   276

12.1.1.1  Business overview 276

12.1.1.2  Products/Solutions/Services offered 277

12.1.1.3  Recent developments           278

12.1.1.3.1                Product enhancements        278

12.1.1.3.2                Deals      278

12.1.1.4  MnM view              279

12.1.1.4.1                Right to win           279

12.1.1.4.2                Strategic choices   279

12.1.1.4.3                Weaknesses and competitive threats 279

12.1.2      AMAZON WEB SERVICES, INC     280

12.1.2.1  Business overview 280

12.1.2.2  Products/Solutions/Services offered 281

12.1.2.3  Recent developments           281

12.1.2.3.1                Product enhancements        281

12.1.2.4  MnM view              282

12.1.2.4.1                Right to win           282

12.1.2.4.2                Strategic choices   282

12.1.2.4.3                Weaknesses and competitive threats 282

12.1.3      TIGERGRAPH     283

12.1.3.1  Business overview 283

12.1.3.2  Products/Solutions/Services offered 283

12.1.3.3  Recent developments           284

12.1.3.3.1                Product enhancements        284

12.1.3.3.2                Deals      284

12.1.3.4  MnM view              285

12.1.3.4.1                Right to win           285

12.1.3.4.2                Strategic choices   285

12.1.3.4.3                Weaknesses and competitive threats 285

12.1.4      GRAPHWISE       286

12.1.4.1  Business overview 286

12.1.4.2  Products/Solutions/Services offered 286

12.1.4.3  Recent developments           287

12.1.4.3.1                Product enhancements        287

12.1.4.4  MnM view              287

12.1.4.4.1                Right to win           287

12.1.4.4.2                Strategic choices   287

12.1.4.4.3                Weaknesses and competitive threats 287

12.1.5      RELATIONALAI 288

12.1.5.1  Business overview 288

12.1.5.2  Products/Solutions/Services offered 288

12.1.5.3  Recent developments           289

12.1.5.3.1                Product launches  289

12.1.5.4  MnM view              289

12.1.5.4.1                Right to win           289

12.1.5.4.2                Strategic choices   289

12.1.5.4.3                Weaknesses and competitive threats 289

12.1.6      IBM        290

12.1.6.1  Business overview 290

12.1.6.2  Products/Solutions/Services offered 291

12.1.6.3  Recent developments           292

12.1.6.3.1                Product enhancements        292

12.1.6.3.2                Deals      292

12.1.7      MICROSOFT       293

12.1.7.1  Business overview 293

12.1.7.2  Products/Solutions/Services offered 295

12.1.7.3  Recent developments           296

12.1.7.3.1                Product enhancements        296

12.1.7.3.2                Deals      296

12.1.8      SAP         297

12.1.8.1  Business overview 297

12.1.8.2  Products/Solutions/Services offered 298

12.1.8.3  Recent developments           299

12.1.8.3.1                Product enhancements        299

12.1.9      ORACLE                300

12.1.9.1  Business overview 300

12.1.9.2  Products/Solutions/Services offered 301

12.1.9.3  Recent developments           302

12.1.9.3.1                Product enhancements        302

12.1.10   STARDOG            303

12.1.10.1                 Business overview 303

12.1.10.2                 Products/Solutions/Services offered 304

12.1.10.3                 Recent developments           304

12.1.10.3.1             Product enhancements        304

12.1.10.3.2             Deals      305

12.1.11   ONTOTEXT        306

12.1.11.1                 Business overview 306

12.1.11.2                 Products/Solutions/Services offered 306

12.1.11.3                 Recent developments           307

12.1.11.3.1             Product enhancements        307

12.1.11.3.2             Deals      308

12.1.12   FRANZ INC.         309

12.1.12.1                 Business overview 309

12.1.12.2                 Products/Solutions/Services offered 309

12.1.12.3                 Recent developments           310

12.1.12.3.1             Product enhancements        310

12.1.13   ALTAIR 311

12.1.13.1                 Business overview 311

12.1.13.2                 Products/Solutions/Services offered 312

12.1.13.3                 Recent developments           313

12.1.13.3.1             Product enhancements        313

12.1.13.3.2             Deals      313

12.1.14   PROGRESS SOFTWARE CORPORATION  314

12.1.15   ESRI       315

12.1.16   SEMANTIC WEB COMPANY          316

12.1.17   OPENLINK SOFTWARE  317

12.2         SMES/START-UPS            318

12.2.1      DATAVID             318

12.2.2      GRAPHBASE       319

12.2.3      CONVERSIGHT 320

12.2.4      ECCENCA             321

12.2.5      ARANGODB        322

12.2.6      FLUREE                 323

12.2.7      DIFFBOT              324

12.2.8      BITNINE               325

12.2.9      MEMGRAPH       326

12.2.10   GRAPHAWARE  327

12.2.11   ONLIM  328

12.2.12   SMABBLER          329

12.2.13   WISECUBE          330

12.2.14   METAPHACTS   331

13            ADJACENT/RELATED MARKETS                332

13.1         INTRODUCTION              332

13.1.1      LIMITATIONS    332

13.2         GRAPH DATABASE MARKET – GLOBAL FORECAST TO 2030        332

13.2.1      MARKET DEFINITION   332

13.2.2      MARKET OVERVIEW       333

13.2.2.1  Graph database market, by offering  333

13.2.2.2  Graph database market, by model type             333

13.2.2.3  Graph database market, by application             334

13.2.2.4  Graph database market, by vertical   335

13.2.2.5  Graph database market, by region     337

13.3         ENTERPRISE CONTENT MANAGEMENT MARKET – GLOBAL FORECAST TO 2029       338

13.3.1      MARKET DEFINITION   338

13.3.2      MARKET OVERVIEW       338

13.3.2.1  Enterprise content management market, by offering     338

13.3.2.2  Enterprise content management market, by business function                 339

13.3.2.3  Enterprise content management market, by deployment mode                 340

13.3.2.4  Enterprise content management market, by organization size                 341

13.3.2.5  Enterprise content management market, by vertical      342

13.3.2.6  Enterprise content management market, by region        343

13.4         GENERATIVE AI MARKET – GLOBAL FORECAST TO 2030                 344

13.4.1      MARKET DEFINITION   344

13.4.2      MARKET OVERVIEW       345

13.4.2.1  Generative AI market, by offering     345

13.4.2.2  Generative AI market, by data modality           346

13.4.2.3  Generative AI market, by application                347

13.4.2.4  Generative AI market, by end user    348

13.4.2.5  Generative AI market, by region        349

14            APPENDIX           351

14.1         DISCUSSION GUIDE        351

14.2         KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL                356

14.3         CUSTOMIZATION OPTIONS        358

14.4         RELATED REPORTS         358

14.5         AUTHOR DETAILS           359

LIST OF TABLES

TABLE 1                USD EXCHANGE RATE, 2021–2023              44

TABLE 2                RISK ASSESSMENT           54

TABLE 3                AVERAGE SELLING PRICE OF KNOWLEDGE GRAPH SOLUTIONS,

BY COUNTRY, 2023           67

TABLE 4                INDICATIVE PRICING ANALYSIS OF KEY PLAYERS              68

TABLE 5                KNOWLEDGE GRAPH MARKET: ECOSYSTEM                 72

TABLE 6                LIST OF MAJOR PATENTS             78

TABLE 7                KNOWLEDGE GRAPH MARKET: CONFERENCES AND EVENTS, 2024–2025                 80

TABLE 8                NORTH AMERICA: REGULATORY BODIES, GOVERNMENT AGENCIES,

AND OTHER ORGANIZATIONS  81

TABLE 9                EUROPE: REGULATORY BODIES, GOVERNMENT AGENCIES,

AND OTHER ORGANIZATIONS  82

TABLE 10              ASIA PACIFIC: REGULATORY BODIES, GOVERNMENT AGENCIES,

AND OTHER ORGANIZATIONS  83

TABLE 11              REST OF THE WORLD: REGULATORY BODIES, GOVERNMENT AGENCIES,

AND OTHER ORGANIZATIONS  84

TABLE 12              IMPACT OF PORTER’S FIVE FORCES ON KNOWLEDGE GRAPH MARKET  91

TABLE 13              INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR

TOP THREE VERTICALS (%)        93

TABLE 14              KEY BUYING CRITERIA FOR TOP THREE VERTICALS         94

TABLE 15              KNOWLEDGE GRAPH MARKET, BY OFFERING, 2019–2023 (USD MILLION)            107

TABLE 16              KNOWLEDGE GRAPH MARKET, BY OFFERING, 2024–2030 (USD MILLION)            108

TABLE 17              KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2019–2023 (USD MILLION)            109

TABLE 18              KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2024–2030 (USD MILLION)            109

TABLE 19              SOLUTIONS: KNOWLEDGE GRAPH MARKET, BY REGION,

2019–2023 (USD MILLION)            109

TABLE 20              SOLUTIONS: KNOWLEDGE GRAPH MARKET, BY REGION,

2024–2030 (USD MILLION)            109

TABLE 21              ENTERPRISE KNOWLEDGE GRAPH PLATFORMS: KNOWLEDGE GRAPH MARKET,

BY REGION, 2019–2023 (USD MILLION)   110

TABLE 22              ENTERPRISE KNOWLEDGE GRAPH PLATFORMS: KNOWLEDGE GRAPH MARKET,

BY REGION, 2024–2030 (USD MILLION)   110

TABLE 23              GRAPH DATABASE ENGINES: KNOWLEDGE GRAPH MARKET,

BY REGION, 2019–2023 (USD MILLION)   111

TABLE 24              GRAPH DATABASE ENGINES: KNOWLEDGE GRAPH MARKET,

BY REGION, 2024–2030 (USD MILLION)   111

TABLE 25              KNOWLEDGE MANAGEMENT TOOLSETS: KNOWLEDGE GRAPH MARKET,

BY REGION, 2019–2023 (USD MILLION)   112

TABLE 26              KNOWLEDGE MANAGEMENT TOOLSETS: KNOWLEDGE GRAPH MARKET,

BY REGION, 2024–2030 (USD MILLION)   112

TABLE 27              KNOWLEDGE GRAPH MARKET, BY SERVICE, 2019–2023 (USD MILLION)            113

TABLE 28              KNOWLEDGE GRAPH MARKET, BY SERVICE, 2024–2030 (USD MILLION)            114

TABLE 29              SERVICES: KNOWLEDGE GRAPH MARKET, BY REGION, 2019–2023 (USD MILLION)          114

TABLE 30              SERVICES: KNOWLEDGE GRAPH MARKET, BY REGION, 2024–2030 (USD MILLION)          114

TABLE 31              PROFESSIONAL SERVICES: KNOWLEDGE GRAPH MARKET,

BY REGION, 2019–2023 (USD MILLION)   115

TABLE 32              PROFESSIONAL SERVICES: KNOWLEDGE GRAPH MARKET,

BY REGION, 2024–2030 (USD MILLION)   115

TABLE 33              MANAGED SERVICES: KNOWLEDGE GRAPH MARKET,

BY REGION, 2019–2023 (USD MILLION)   116

TABLE 34              MANAGED SERVICES: KNOWLEDGE GRAPH MARKET,

BY REGION, 2024–2030 (USD MILLION)   116

TABLE 35             KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2019–2023 (USD MILLION)            119

TABLE 36             KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2024–2030 (USD MILLION)            119

TABLE 37              RESOURCE DESCRIPTION FRAMEWORK (RDF) TRIPLE STORES: KNOWLEDGE GRAPH MARKET, BY REGION, 2019–2023 (USD MILLION)            119

TABLE 38              RESOURCE DESCRIPTION FRAMEWORK (RDF) TRIPLE STORES: KNOWLEDGE GRAPH MARKET, BY REGION, 2024–2030 (USD MILLION)            120

TABLE 39              LABELED PROPERTY GRAPH (LPG): KNOWLEDGE GRAPH MARKET,

BY REGION, 2019–2023 (USD MILLION)   120

TABLE 40              LABELED PROPERTY GRAPH (LPG): KNOWLEDGE GRAPH MARKET,

BY REGION, 2024–2030 (USD MILLION)   121

TABLE 41              KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2019–2023 (USD MILLION)              124

TABLE 42              KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2024–2030 (USD MILLION)              124

TABLE 43              DATA GOVERNANCE & MASTER DATA MANAGEMENT: KNOWLEDGE GRAPH MARKET, BY REGION, 2019–2023 (USD MILLION)            125

TABLE 44              DATA GOVERNANCE & MASTER DATA MANAGEMENT: KNOWLEDGE GRAPH MARKET, BY REGION, 2024–2030 (USD MILLION)            125

TABLE 45              DATA ANALYTICS & BUSINESS INTELLIGENCE: KNOWLEDGE GRAPH MARKET,

BY REGION, 2019–2023 (USD MILLION)   126

TABLE 46              DATA ANALYTICS & BUSINESS INTELLIGENCE: KNOWLEDGE GRAPH MARKET,

BY REGION, 2024–2030 (USD MILLION)   126

TABLE 47              KNOWLEDGE & CONTENT MANAGEMENT: KNOWLEDGE GRAPH MARKET,

BY REGION, 2019–2023 (USD MILLION)   127

TABLE 48              KNOWLEDGE & CONTENT MANAGEMENT: KNOWLEDGE GRAPH MARKET,

BY REGION, 2024–2030 (USD MILLION)   127

TABLE 49              VIRTUAL ASSISTANTS, SELF-SERVICE DATA, AND DIGITAL ASSET DISCOVERY: KNOWLEDGE GRAPH MARKET, BY REGION, 2019–2023 (USD MILLION)                128

TABLE 50              VIRTUAL ASSISTANTS, SELF-SERVICE DATA, AND DIGITAL ASSET DISCOVERY: KNOWLEDGE GRAPH MARKET, BY REGION, 2024–2030 (USD MILLION)                128

TABLE 51              PRODUCT & CONFIGURATION MANAGEMENT: KNOWLEDGE GRAPH MARKET,

BY REGION, 2019–2023 (USD MILLION)   129

TABLE 52              PRODUCT & CONFIGURATION MANAGEMENT: KNOWLEDGE GRAPH MARKET,

BY REGION, 2024–2030 (USD MILLION)   129

TABLE 53              INFRASTRUCTURE & ASSET MANAGEMENT: KNOWLEDGE GRAPH MARKET,

BY REGION, 2019–2023 (USD MILLION)   130

TABLE 54              INFRASTRUCTURE & ASSET MANAGEMENT: KNOWLEDGE GRAPH MARKET,

BY REGION, 2024–2030 (USD MILLION)   130

TABLE 55              PROCESS OPTIMIZATION & RESOURCE MANAGEMENT:

KNOWLEDGE GRAPH MARKET, BY REGION, 2019–2023 (USD MILLION)            131

TABLE 56              PROCESS OPTIMIZATION & RESOURCE MANAGEMENT:

KNOWLEDGE GRAPH MARKET, BY REGION, 2024–2030 (USD MILLION)            131

TABLE 57              RISK MANAGEMENT, COMPLIANCE, AND REGULATORY REPORTING:

KNOWLEDGE GRAPH MARKET, BY REGION, 2019–2023 (USD MILLION)            132

TABLE 58              RISK MANAGEMENT, COMPLIANCE, AND REGULATORY REPORTING:

KNOWLEDGE GRAPH MARKET, BY REGION, 2024–2030 (USD MILLION)            132

TABLE 59              MARKET & CUSTOMER INTELLIGENCE AND SALES OPTIMIZATION:

KNOWLEDGE GRAPH MARKET, BY REGION, 2019–2023 (USD MILLION)            133

TABLE 60              MARKET & CUSTOMER INTELLIGENCE AND SALES OPTIMIZATION:

KNOWLEDGE GRAPH MARKET, BY REGION, 2024–2030 (USD MILLION)            133

TABLE 61              OTHER APPLICATIONS: KNOWLEDGE GRAPH MARKET,

BY REGION, 2019–2023 (USD MILLION)   134

TABLE 62              OTHER APPLICATIONS: KNOWLEDGE GRAPH MARKET,

BY REGION, 2024–2030 (USD MILLION)   134

TABLE 63              KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2019–2023 (USD MILLION)            137

TABLE 64              KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2024–2030 (USD MILLION)            138

TABLE 65             BFSI: KNOWLEDGE GRAPH MARKET, BY REGION, 2019–2023 (USD MILLION)            139

TABLE 66             BFSI: KNOWLEDGE GRAPH MARKET, BY REGION, 2024–2030 (USD MILLION)            139

TABLE 67              RETAIL & ECOMMERCE: KNOWLEDGE GRAPH MARKET,

BY REGION, 2019–2023 (USD MILLION)   144

TABLE 68              RETAIL & ECOMMERCE: KNOWLEDGE GRAPH MARKET,

BY REGION, 2024–2030 (USD MILLION)   145

TABLE 69              HEALTHCARE, LIFE SCIENCES, AND PHARMACEUTICALS:

KNOWLEDGE GRAPH MARKET, BY REGION, 2019–2023 (USD MILLION)            150

TABLE 70              HEALTHCARE, LIFE SCIENCES, AND PHARMACEUTICALS:

KNOWLEDGE GRAPH MARKET, BY REGION, 2024–2030 (USD MILLION)            150

TABLE 71              TELECOM & TECHNOLOGY: KNOWLEDGE GRAPH MARKET,

BY REGION, 2019–2023 (USD MILLION)   154

TABLE 72              TELECOM & TECHNOLOGY: KNOWLEDGE GRAPH MARKET,

BY REGION, 2024–2030 (USD MILLION)   154

TABLE 73              GOVERNMENT: KNOWLEDGE GRAPH MARKET,

BY REGION, 2019–2023 (USD MILLION)   158

TABLE 74              GOVERNMENT: KNOWLEDGE GRAPH MARKET,

BY REGION, 2024–2030 (USD MILLION)   158

TABLE 75              MANUFACTURING & AUTOMOTIVE: KNOWLEDGE GRAPH MARKET,

BY REGION, 2019–2023 (USD MILLION)   161

TABLE 76              MANUFACTURING & AUTOMOTIVE: KNOWLEDGE GRAPH MARKET,

BY REGION, 2024–2030 (USD MILLION)   162

TABLE 77              MEDIA & ENTERTAINMENT: KNOWLEDGE GRAPH MARKET,

BY REGION, 2019–2023 (USD MILLION)   165

TABLE 78              MEDIA & ENTERTAINMENT: KNOWLEDGE GRAPH MARKET,

BY REGION, 2024–2030 (USD MILLION)   166

TABLE 79              ENERGY, UTILITIES, AND INFRASTRUCTURE: KNOWLEDGE GRAPH MARKET,

BY REGION, 2019–2023 (USD MILLION)   170

TABLE 80              ENERGY, UTILITIES, AND INFRASTRUCTURE: KNOWLEDGE GRAPH MARKET,

BY REGION, 2024–2030 (USD MILLION)   170

TABLE 81              TRAVEL & HOSPITALITY: KNOWLEDGE GRAPH MARKET,

BY REGION, 2019–2023 (USD MILLION)   173

TABLE 82              TRAVEL & HOSPITALITY: KNOWLEDGE GRAPH MARKET,

BY REGION, 2024–2030 (USD MILLION)   174

TABLE 83              TRANSPORTATION & LOGISTICS: KNOWLEDGE GRAPH MARKET,

BY REGION, 2019–2023 (USD MILLION)   176

TABLE 84              TRANSPORTATION & LOGISTICS: KNOWLEDGE GRAPH MARKET,

BY REGION, 2024–2030 (USD MILLION)   176

TABLE 85              OTHER VERTICALS: KNOWLEDGE GRAPH MARKET,

BY REGION, 2019–2023 (USD MILLION)   179

TABLE 86              OTHER VERTICALS: KNOWLEDGE GRAPH MARKET,

BY REGION, 2024–2030 (USD MILLION)   179

TABLE 87              KNOWLEDGE GRAPH MARKET, BY REGION, 2019–2023 (USD MILLION)            181

TABLE 88              KNOWLEDGE GRAPH MARKET, BY REGION, 2024–2030 (USD MILLION)            181

TABLE 89              NORTH AMERICA: KNOWLEDGE GRAPH MARKET,

BY OFFERING, 2019–2023 (USD MILLION)               183

TABLE 90              NORTH AMERICA: KNOWLEDGE GRAPH MARKET,

BY OFFERING, 2024–2030 (USD MILLION)               184

TABLE 91              NORTH AMERICA: KNOWLEDGE GRAPH MARKET,

BY SOLUTION, 2019–2023 (USD MILLION)              184

TABLE 92              NORTH AMERICA: KNOWLEDGE GRAPH MARKET,

BY SOLUTION, 2024–2030 (USD MILLION)              184

TABLE 93              NORTH AMERICA: KNOWLEDGE GRAPH MARKET,

BY SERVICE, 2019–2023 (USD MILLION)  184

TABLE 94              NORTH AMERICA: KNOWLEDGE GRAPH MARKET,

BY SERVICE, 2024–2030 (USD MILLION)  185

TABLE 95              NORTH AMERICA: KNOWLEDGE GRAPH MARKET,

BY MODEL TYPE, 2019–2023 (USD MILLION)        185

TABLE 96              NORTH AMERICA: KNOWLEDGE GRAPH MARKET,

BY MODEL TYPE, 2024–2030 (USD MILLION)        185

TABLE 97              NORTH AMERICA: KNOWLEDGE GRAPH MARKET,

BY APPLICATION, 2019–2023 (USD MILLION)       186

TABLE 98              NORTH AMERICA: KNOWLEDGE GRAPH MARKET,

BY APPLICATION, 2024–2030 (USD MILLION)       186

TABLE 99              NORTH AMERICA: KNOWLEDGE GRAPH MARKET,

BY VERTICAL, 2019–2023 (USD MILLION)               187

TABLE 100            NORTH AMERICA: KNOWLEDGE GRAPH MARKET,

BY VERTICAL, 2024–2030 (USD MILLION)               187

TABLE 101            NORTH AMERICA: KNOWLEDGE GRAPH MARKET,

BY COUNTRY, 2019–2023 (USD MILLION)               188

TABLE 102            NORTH AMERICA: KNOWLEDGE GRAPH MARKET,

BY COUNTRY, 2024–2030 (USD MILLION)               188

TABLE 103            US: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2019–2023 (USD MILLION)     189

TABLE 104            US: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2024–2030 (USD MILLION)     189

TABLE 105            US: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2019–2023 (USD MILLION)    189

TABLE 106            US: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2024–2030 (USD MILLION)    189

TABLE 107            US: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2019–2023 (USD MILLION)            190

TABLE 108            US: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2024–2030 (USD MILLION)            190

TABLE 109            US: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2019–2023 (USD MILLION)                190

TABLE 110            US: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2024–2030 (USD MILLION)                190

TABLE 111            US: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2019–2023 (USD MILLION)              191

TABLE 112            US: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2024–2030 (USD MILLION)              191

TABLE 113            US: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2019–2023 (USD MILLION)     192

TABLE 114            US: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2024–2030 (USD MILLION)     192

TABLE 115            EUROPE: KNOWLEDGE GRAPH MARKET,

BY OFFERING, 2019–2023 (USD MILLION)               194

TABLE 116            EUROPE: KNOWLEDGE GRAPH MARKET,

BY OFFERING, 2024–2030 (USD MILLION)               194

TABLE 117            EUROPE: KNOWLEDGE GRAPH MARKET,

BY SOLUTION, 2019–2023 (USD MILLION)              194

TABLE 118            EUROPE: KNOWLEDGE GRAPH MARKET,

BY SOLUTION, 2024–2030 (USD MILLION)              195

TABLE 119            EUROPE: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2019–2023 (USD MILLION)         195

TABLE 120            EUROPE: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2024–2030 (USD MILLION)         195

TABLE 121            EUROPE: KNOWLEDGE GRAPH MARKET,

BY MODEL TYPE, 2019–2023 (USD MILLION)        195

TABLE 122            EUROPE: KNOWLEDGE GRAPH MARKET,

BY MODEL TYPE, 2024–2030 (USD MILLION)        196

TABLE 123            EUROPE: KNOWLEDGE GRAPH MARKET,

BY APPLICATION, 2019–2023 (USD MILLION)       196

TABLE 124            EUROPE: KNOWLEDGE GRAPH MARKET,

BY APPLICATION, 2024–2030 (USD MILLION)       197

TABLE 125            EUROPE: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2019–2023 (USD MILLION)     197

TABLE 126            EUROPE: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2024–2030 (USD MILLION)     198

TABLE 127            EUROPE: KNOWLEDGE GRAPH MARKET, BY COUNTRY, 2019–2023 (USD MILLION)     198

TABLE 128            EUROPE: KNOWLEDGE GRAPH MARKET, BY COUNTRY, 2024–2030 (USD MILLION)     199

TABLE 129            UK: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2019–2023 (USD MILLION)     200

TABLE 130            UK: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2024–2030 (USD MILLION)     200

TABLE 131            UK: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2019–2023 (USD MILLION)    200

TABLE 132            UK: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2024–2030 (USD MILLION)    200

TABLE 133            UK: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2019–2023 (USD MILLION)            201

TABLE 134            UK: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2024–2030 (USD MILLION)            201

TABLE 135            UK: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2019–2023 (USD MILLION)                201

TABLE 136            UK: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2024–2030 (USD MILLION)                201

TABLE 137            UK: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2019–2023 (USD MILLION)              202

TABLE 138            UK: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2024–2030 (USD MILLION)              202

TABLE 139            UK: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2019–2023 (USD MILLION)     203

TABLE 140            UK: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2024–2030 (USD MILLION)     203

TABLE 141            ITALY: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2019–2023 (USD MILLION)     205

TABLE 142            ITALY: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2024–2030 (USD MILLION)     205

TABLE 143            ITALY: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2019–2023 (USD MILLION)    205

TABLE 144            ITALY: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2024–2030 (USD MILLION)    206

TABLE 145            ITALY: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2019–2023 (USD MILLION)         206

TABLE 146            ITALY: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2024–2030 (USD MILLION)         206

TABLE 147            ITALY: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE,

2019–2023 (USD MILLION)            206

TABLE 148            ITALY: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE,

2024–2030 (USD MILLION)            207

TABLE 149            ITALY: KNOWLEDGE GRAPH MARKET, BY APPLICATION,

2019–2023 (USD MILLION)            207

TABLE 150            ITALY: KNOWLEDGE GRAPH MARKET, BY APPLICATION,

2024–2030 (USD MILLION)            208

TABLE 151            ITALY: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2019–2023 (USD MILLION)     208

TABLE 152            ITALY: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2024–2030 (USD MILLION)     209

TABLE 153            ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY OFFERING,

2019–2023 (USD MILLION)            212

TABLE 154            ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY OFFERING,

2024–2030 (USD MILLION)            213

TABLE 155            ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY SOLUTION,

2019–2023 (USD MILLION)            213

TABLE 156            ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY SOLUTION,

2024–2030 (USD MILLION)            213

TABLE 157            ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY SERVICE,

2019–2023 (USD MILLION)            213

TABLE 158            ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY SERVICE,

2024–2030 (USD MILLION)            214

TABLE 159            ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE,

2019–2023 (USD MILLION)            214

TABLE 160            ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE,

2024–2030 (USD MILLION)            214

TABLE 161            ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY APPLICATION,

2019–2023 (USD MILLION)            215

TABLE 162            ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY APPLICATION,

2024–2030 (USD MILLION)            215

TABLE 163            ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY VERTICAL,

2019–2023 (USD MILLION)            216

TABLE 164            ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY VERTICAL,

2024–2030 (USD MILLION)            216

TABLE 165            ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY COUNTRY,

2019–2023 (USD MILLION)            217

TABLE 166            ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY COUNTRY,

2024–2030 (USD MILLION)            217

TABLE 167            CHINA: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2019–2023 (USD MILLION)     218

TABLE 168            CHINA: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2024–2030 (USD MILLION)     218

TABLE 169            CHINA: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2019–2023 (USD MILLION)    218

TABLE 170            CHINA: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2024–2030 (USD MILLION)    218

TABLE 171            CHINA: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2019–2023 (USD MILLION)         219

TABLE 172            CHINA: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2024–2030 (USD MILLION)         219

TABLE 173            CHINA: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE,

2019–2023 (USD MILLION)            219

TABLE 174            CHINA: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE,

2024–2030 (USD MILLION)            219

TABLE 175            CHINA: KNOWLEDGE GRAPH MARKET, BY APPLICATION,

2019–2023 (USD MILLION)            220

TABLE 176            CHINA: KNOWLEDGE GRAPH MARKET, BY APPLICATION,

2024–2030 (USD MILLION)            220

TABLE 177            CHINA: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2019–2023 (USD MILLION)     221

TABLE 178            CHINA: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2024–2030 (USD MILLION)     221

TABLE 179            INDIA: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2019–2023 (USD MILLION)     223

TABLE 180            INDIA: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2024–2030 (USD MILLION)     223

TABLE 181            INDIA: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2019–2023 (USD MILLION)    223

TABLE 182            INDIA: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2024–2030 (USD MILLION)    223

TABLE 183            INDIA: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2019–2023 (USD MILLION)         224

TABLE 184            INDIA: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2024–2030 (USD MILLION)         224

TABLE 185            INDIA: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE,

2019–2023 (USD MILLION)            224

TABLE 186            INDIA: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE,

2024–2030 (USD MILLION)            224

TABLE 187            INDIA: KNOWLEDGE GRAPH MARKET, BY APPLICATION,

2019–2023 (USD MILLION)            225

TABLE 188            INDIA: KNOWLEDGE GRAPH MARKET, BY APPLICATION,

2024–2030 (USD MILLION)            225

TABLE 189            INDIA: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2019–2023 (USD MILLION)     226

TABLE 190            INDIA: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2024–2030 (USD MILLION)     226

TABLE 191            MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET,

BY OFFERING, 2019–2023 (USD MILLION)               229

TABLE 192            MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET,

BY OFFERING, 2024–2030 (USD MILLION)               229

TABLE 193            MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET,

BY SOLUTION, 2019–2023 (USD MILLION)              229

TABLE 194            MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET,

BY SOLUTION, 2024–2030 (USD MILLION)              229

TABLE 195            MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET,

BY SERVICE, 2019–2023 (USD MILLION)  230

TABLE 196            MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET,

BY SERVICE, 2024–2030 (USD MILLION)  230

TABLE 197            MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET,

BY MODEL TYPE, 2019–2023 (USD MILLION)        230

TABLE 198            MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET,

BY MODEL TYPE, 2024–2030 (USD MILLION)        230

TABLE 199            MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET,

BY APPLICATION, 2019–2023 (USD MILLION)       231

TABLE 200            MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET,

BY APPLICATION, 2024–2030 (USD MILLION)       231

TABLE 201            MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET,

BY VERTICAL, 2019–2023 (USD MILLION)               232

TABLE 202            MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET,

BY VERTICAL, 2024–2030 (USD MILLION)               232

TABLE 203            MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET,

BY REGION, 2019–2023 (USD MILLION)   233

TABLE 204            MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET,

BY REGION, 2024–2030 (USD MILLION)   233

TABLE 205            GCC COUNTRIES: KNOWLEDGE GRAPH MARKET,

BY OFFERING, 2019–2023 (USD MILLION)               234

TABLE 206            GCC COUNTRIES: KNOWLEDGE GRAPH MARKET,

BY OFFERING, 2024–2030 (USD MILLION)               234

TABLE 207            GCC COUNTRIES: KNOWLEDGE GRAPH MARKET,

BY SOLUTION, 2019–2023 (USD MILLION)              234

TABLE 208            GCC COUNTRIES: KNOWLEDGE GRAPH MARKET,

BY SOLUTION, 2024–2030 (USD MILLION)              234

TABLE 209            GCC COUNTRIES: KNOWLEDGE GRAPH MARKET,

BY SERVICE, 2019–2023 (USD MILLION)  235

TABLE 210            GCC COUNTRIES: KNOWLEDGE GRAPH MARKET,

BY SERVICE, 2024–2030 (USD MILLION)  235

TABLE 211            GCC COUNTRIES: KNOWLEDGE GRAPH MARKET,

BY MODEL TYPE, 2019–2023 (USD MILLION)        235

TABLE 212            GCC COUNTRIES: KNOWLEDGE GRAPH MARKET,

BY MODEL TYPE, 2024–2030 (USD MILLION)        235

TABLE 213            GCC COUNTRIES: KNOWLEDGE GRAPH MARKET,

BY APPLICATION, 2019–2023 (USD MILLION)       236

TABLE 214            GCC COUNTRIES: KNOWLEDGE GRAPH MARKET,

BY APPLICATION, 2024–2030 (USD MILLION)       236

TABLE 215            GCC COUNTRIES: KNOWLEDGE GRAPH MARKET,

BY VERTICAL, 2019–2023 (USD MILLION)               237

TABLE 216            GCC COUNTRIES: KNOWLEDGE GRAPH MARKET,

BY VERTICAL, 2024–2030 (USD MILLION)               237

TABLE 217            GCC COUNTRIES: KNOWLEDGE GRAPH MARKET,

BY REGION, 2019–2023 (USD MILLION)   238

TABLE 218            GCC COUNTRIES: KNOWLEDGE GRAPH MARKET,

BY REGION, 2024–2030 (USD MILLION)   238

TABLE 219            KSA: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2019–2023 (USD MILLION)     239

TABLE 220            KSA: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2024–2030 (USD MILLION)     239

TABLE 221            KSA: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2019–2023 (USD MILLION)    240

TABLE 222            KSA: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2024–2030 (USD MILLION)    240

TABLE 223          KSA: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2019–2023 (USD MILLION)            240

TABLE 224          KSA: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2024–2030 (USD MILLION)            240

TABLE 225            KSA: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2019–2023 (USD MILLION)                241

TABLE 226            KSA: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2024–2030 (USD MILLION)                241

TABLE 227            KSA: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2019–2023 (USD MILLION)              241

TABLE 228            KSA: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2024–2030 (USD MILLION)              242

TABLE 229            KSA: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2019–2023 (USD MILLION)     242

TABLE 230            KSA: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2024–2030 (USD MILLION)     243

TABLE 231          LATIN AMERICA: KNOWLEDGE GRAPH MARKET,

BY OFFERING, 2019–2023 (USD MILLION)               245

TABLE 232          LATIN AMERICA: KNOWLEDGE GRAPH MARKET,

BY OFFERING, 2024–2030 (USD MILLION)               245

TABLE 233          LATIN AMERICA: KNOWLEDGE GRAPH MARKET,

BY SOLUTION, 2019–2023 (USD MILLION)              245

TABLE 234          LATIN AMERICA: KNOWLEDGE GRAPH MARKET,

BY SOLUTION, 2024–2030 (USD MILLION)              246

TABLE 235          LATIN AMERICA: KNOWLEDGE GRAPH MARKET,

BY SERVICE, 2019–2023 (USD MILLION)  246

TABLE 236          LATIN AMERICA: KNOWLEDGE GRAPH MARKET,

BY SERVICE, 2024–2030 (USD MILLION)  246

TABLE 237          LATIN AMERICA: KNOWLEDGE GRAPH MARKET,

BY MODEL TYPE, 2019–2023 (USD MILLION)        246

TABLE 238          LATIN AMERICA: KNOWLEDGE GRAPH MARKET,

BY MODEL TYPE, 2024–2030 (USD MILLION)        247

TABLE 239          LATIN AMERICA: KNOWLEDGE GRAPH MARKET,

BY APPLICATION, 2019–2023 (USD MILLION)       247

TABLE 240          LATIN AMERICA: KNOWLEDGE GRAPH MARKET,

BY APPLICATION, 2024–2030 (USD MILLION)       248

TABLE 241          LATIN AMERICA: KNOWLEDGE GRAPH MARKET,

BY VERTICAL, 2019–2023 (USD MILLION)               248

TABLE 242          LATIN AMERICA: KNOWLEDGE GRAPH MARKET,

BY VERTICAL, 2024–2030 (USD MILLION)               249

TABLE 243          LATIN AMERICA: KNOWLEDGE GRAPH MARKET,

BY COUNTRY, 2019–2023 (USD MILLION)               249

TABLE 244          LATIN AMERICA: KNOWLEDGE GRAPH MARKET,

BY COUNTRY, 2024–2030 (USD MILLION)               249

TABLE 245            BRAZIL: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2019–2023 (USD MILLION)     250

TABLE 246            BRAZIL: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2024–2030 (USD MILLION)     250

TABLE 247            BRAZIL: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2019–2023 (USD MILLION)    250

TABLE 248            BRAZIL: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2024–2030 (USD MILLION)    251

TABLE 249            BRAZIL: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2019–2023 (USD MILLION)         251

TABLE 250            BRAZIL: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2024–2030 (USD MILLION)         251

TABLE 251            BRAZIL: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE,

2019–2023 (USD MILLION)            251

TABLE 252            BRAZIL: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE,

2024–2030 (USD MILLION)            252

TABLE 253            BRAZIL: KNOWLEDGE GRAPH MARKET, BY APPLICATION,

2019–2023 (USD MILLION)            252

TABLE 254            BRAZIL: KNOWLEDGE GRAPH MARKET, BY APPLICATION,

2024–2030 (USD MILLION)            253

TABLE 255            BRAZIL: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2019–2023 (USD MILLION)     253

TABLE 256            BRAZIL: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2024–2030 (USD MILLION)     254

TABLE 257            OVERVIEW OF STRATEGIES ADOPTED BY KEY KNOWLEDGE GRAPH MARKET VENDORS             256

TABLE 258            KNOWLEDGE GRAPH MARKET: DEGREE OF COMPETITION 258

TABLE 259            KNOWLEDGE GRAPH MARKET: VERTICAL FOOTPRINT       263

TABLE 260            KNOWLEDGE GRAPH MARKET: OFFERING FOOTPRINT       264

TABLE 261            KNOWLEDGE GRAPH MARKET: REGIONAL FOOTPRINT       265

TABLE 262            KNOWLEDGE GRAPH MARKET: DETAILED LIST OF KEY START-UPS/SMES            267

TABLE 263            KNOWLEDGE GRAPH MARKET: COMPETITIVE BENCHMARKING

OF KEY START-UPS/SMES            268

TABLE 264            KNOWLEDGE GRAPH MARKET: PRODUCT LAUNCHES & ENHANCEMENTS,

APRIL 2022–DECEMBER 2024        269

TABLE 265            KNOWLEDGE GRAPH MARKET: DEALS, APRIL 2022–DECEMBER 2024     272

TABLE 266            NEO4J: COMPANY OVERVIEW    276

TABLE 267            NEO4J: PRODUCTS/SOLUTIONS/SERVICES OFFERED             277

TABLE 268            NEO4J: PRODUCT ENHANCEMENTS        278

TABLE 269            NEO4J: DEALS   278

TABLE 270            AMAZON WEB SERVICES, INC: COMPANY OVERVIEW          280

TABLE 271            AMAZON WEB SERVICES, INC: PRODUCTS/SOLUTIONS/SERVICES OFFERED    281

TABLE 272            AMAZON WEB SERVICES, INC: PRODUCT ENHANCEMENTS             281

TABLE 273            TIGERGRAPH: COMPANY OVERVIEW     283

TABLE 274            TIGERGRAPH: PRODUCTS/SOLUTIONS/SERVICES OFFERED    283

TABLE 275            TIGERGRAPH: PRODUCT ENHANCEMENTS                 284

TABLE 276            TIGERGRAPH: DEALS     284

TABLE 277            GRAPHWISE: COMPANY OVERVIEW        286

TABLE 278            GRAPHWISE: PRODUCTS/SOLUTIONS/SERVICES OFFERED    286

TABLE 279            GRAPHWISE: PRODUCT ENHANCEMENTS                 287

TABLE 280            RELATIONALAI: COMPANY OVERVIEW 288

TABLE 281            RELATIONALAI: PRODUCTS/SOLUTIONS/SERVICES OFFERED    288

TABLE 282            RELATIONALAI: PRODUCT LAUNCHES  289

TABLE 283            IBM: COMPANY OVERVIEW         290

TABLE 284            IBM: PRODUCTS/SOLUTIONS/SERVICES OFFERED             291

TABLE 285            IBM: PRODUCT ENHANCEMENTS             292

TABLE 286            IBM: DEALS        292

TABLE 287            MICROSOFT: COMPANY OVERVIEW        293

TABLE 288            MICROSOFT: PRODUCTS/SOLUTIONS/SERVICES OFFERED    295

TABLE 289            MICROSOFT: PRODUCT ENHANCEMENTS                 296

TABLE 290            MICROSOFT: DEALS       296

TABLE 291            SAP: COMPANY OVERVIEW         297

TABLE 292            SAP: PRODUCTS/SOLUTIONS/SERVICES OFFERED             298

TABLE 293            SAP: PRODUCT ENHANCEMENTS             299

TABLE 294            ORACLE: COMPANY OVERVIEW                300

TABLE 295            ORACLE: PRODUCTS/SOLUTIONS/SERVICES OFFERED             301

TABLE 296            ORACLE: PRODUCT ENHANCEMENTS   302

TABLE 297            STARDOG: COMPANY OVERVIEW             303

TABLE 298            STARDOG: PRODUCTS/SOLUTIONS/SERVICES OFFERED             304

TABLE 299            STARDOG: PRODUCT ENHANCEMENTS                 304

TABLE 300            STARDOG: DEALS            305

TABLE 301            ONTOTEXT: COMPANY OVERVIEW         306

TABLE 302            ONTOTEXT: PRODUCTS/SOLUTIONS/SERVICES OFFERED    306

TABLE 303            ONTOTEXT: PRODUCT ENHANCEMENTS                 307

TABLE 304            ONTOTEXT: DEALS        308

TABLE 305            FRANZ INC.: COMPANY OVERVIEW          309

TABLE 306            FRANZ INC.: PRODUCTS/SOLUTIONS/SERVICES OFFERED             309

TABLE 307            FRANZ INC.: PRODUCT ENHANCEMENTS                 310

TABLE 308            ALTAIR: COMPANY OVERVIEW 311

TABLE 309            ALTAIR: PRODUCTS/SOLUTIONS/SERVICES OFFERED             312

TABLE 310            ALTAIR: PRODUCT ENHANCEMENTS     313

TABLE 311            ALTAIR: DEALS 313

TABLE 312            ADJACENT REPORTS      332

TABLE 313            GRAPH DATABASE MARKET, BY OFFERING, 2019–2023 (USD MILLION)            333

TABLE 314            GRAPH DATABASE MARKET, BY OFFERING, 2024–2030 (USD MILLION)            333

TABLE 315            GRAPH DATABASE MARKET, BY MODEL TYPE, 2019–2023 (USD MILLION)            334

TABLE 316            GRAPH DATABASE MARKET, BY MODEL TYPE, 2024–2030 (USD MILLION)            334

TABLE 317            GRAPH DATABASE MARKET, BY APPLICATION, 2019–2023 (USD MILLION)            334

TABLE 318            GRAPH DATABASE MARKET, BY APPLICATION, 2024–2030 (USD MILLION)            335

TABLE 319            GRAPH DATABASE MARKET, BY VERTICAL, 2019–2023 (USD MILLION)            336

TABLE 320            GRAPH DATABASE MARKET, BY VERTICAL, 2024–2030 (USD MILLION)            336

TABLE 321            GRAPH DATABASE MARKET, BY REGION, 2019–2023 (USD MILLION)       337

TABLE 322            GRAPH DATABASE MARKET, BY REGION, 2024–2030 (USD MILLION)       337

TABLE 323            ENTERPRISE CONTENT MANAGEMENT MARKET, BY OFFERING,

2019–2023 (USD MILLION)            339

TABLE 324            ENTERPRISE CONTENT MANAGEMENT MARKET, BY OFFERING,

2024–2029 (USD MILLION)            339

TABLE 325            ENTERPRISE CONTENT MANAGEMENT MARKET, BY BUSINESS FUNCTION,

2019–2023 (USD MILLION)            339

TABLE 326            ENTERPRISE CONTENT MANAGEMENT MARKET, BY BUSINESS FUNCTION,

2024–2029 (USD MILLION)            340

TABLE 327            ENTERPRISE CONTENT MANAGEMENT MARKET, BY DEPLOYMENT MODE,

2019–2023 (USD MILLION)            340

TABLE 328            ENTERPRISE CONTENT MANAGEMENT MARKET, BY DEPLOYMENT MODE,

2024–2029 (USD MILLION)            341

TABLE 329            ENTERPRISE CONTENT MANAGEMENT MARKET, BY ORGANIZATION SIZE,

2019–2023 (USD MILLION)            341

TABLE 330            ENTERPRISE CONTENT MANAGEMENT MARKET, BY ORGANIZATION SIZE,

2024–2029 (USD MILLION)            341

TABLE 331            ENTERPRISE CONTENT MANAGEMENT MARKET, BY VERTICAL,

2019–2023 (USD MILLION)            342

TABLE 332            ENTERPRISE CONTENT MANAGEMENT MARKET, BY VERTICAL,

2024–2029 (USD MILLION)            343

TABLE 333            ENTERPRISE CONTENT MANAGEMENT MARKET, BY REGION,

2019–2023 (USD MILLION)            344

TABLE 334            ENTERPRISE CONTENT MANAGEMENT MARKET, BY REGION,

2024–2029 (USD MILLION)            344

TABLE 335            GENERATIVE AI MARKET, BY OFFERING, 2019–2023 (USD MILLION)       345

TABLE 336            GENERATIVE AI MARKET, BY OFFERING, 2024–2030 (USD MILLION)       346

TABLE 337            GENERATIVE AI MARKET, BY DATA MODALITY, 2019–2023 (USD MILLION)            346

TABLE 338            GENERATIVE AI MARKET, BY DATA MODALITY, 2024–2030 (USD MILLION)            347

TABLE 339            GENERATIVE AI MARKET, BY APPLICATION, 2019–2023 (USD MILLION)            347

TABLE 340            GENERATIVE AI MARKET, BY APPLICATION, 2024–2030 (USD MILLION)            348

TABLE 341            GENERATIVE AI MARKET, BY END USER, 2019–2023 (USD MILLION)       348

TABLE 342            GENERATIVE AI MARKET, BY END USER, 2024–2030 (USD MILLION)       349

TABLE 343            GENERATIVE AI MARKET, BY REGION, 2019–2023 (USD MILLION) 349

TABLE 344            GENERATIVE AI MARKET, BY REGION, 2024–2030 (USD MILLION) 350

LIST OF FIGURES

FIGURE 1              KNOWLEDGE GRAPH MARKET: RESEARCH DESIGN                45

FIGURE 2              TOP-DOWN AND APPROACH     49

FIGURE 3              APPROACH 1 (SUPPLY SIDE): REVENUE OF VENDORS IN KNOWLEDGE

GRAPH MARKET               49

FIGURE 4              BOTTOM-UP APPROACH              50

FIGURE 5              DEMAND-SIDE ANALYSIS             50

FIGURE 6              BOTTOM-UP (SUPPLY SIDE) ANALYSIS: COLLECTIVE REVENUE FROM SOLUTIONS/SERVICES OF KNOWLEDGE GRAPH MARKET  51

FIGURE 7              DATA TRIANGULATION                52

FIGURE 8              KNOWLEDGE GRAPH MARKET, 2022–2030 (USD MILLION)            56

FIGURE 9              KNOWLEDGE GRAPH MARKET: REGIONAL SNAPSHOT          56

FIGURE 10            GROWING NEED FOR ADVANCED DATA INTEGRATION, CONTEXTUAL INSIGHTS,

AND AI-DRIVEN DECISION-MAKING TO DRIVE KNOWLEDGE GRAPH MARKET               58

FIGURE 11            SOLUTIONS SEGMENT TO ACCOUNT FOR LARGER MARKET SHARE IN 2024               58

FIGURE 12            MANAGED SERVICES SEGMENT TO REGISTER HIGHER CAGR DURING

FORECAST PERIOD         59

FIGURE 13            LABELED PROPERTY GRAPH (LPG) TO GROW FASTER DURING FORECAST PERIOD      59

FIGURE 14            DATA ANALYTICS & BUSINESS INTELLIGENCE SEGMENT TO DOMINATE IN 2024             60

FIGURE 15            BFSI SEGMENT TO ACCOUNT FOR MAJOR SHARE IN 2024   60

FIGURE 16            GRAPH DATABASE ENGINE AND PROFESSIONAL SERVICES – DOMINANT SEGMENTS IN 2024                 61

FIGURE 17            KNOWLEDGE GRAPH MARKET: DRIVERS, RESTRAINTS, OPPORTUNITIES,

AND CHALLENGES          62

FIGURE 18            TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS   66

FIGURE 19            AVERAGE SELLING PRICE TREND OF KEY PLAYERS, BY COUNTRY, 2023      67

FIGURE 20            KNOWLEDGE GRAPH MARKET: SUPPLY CHAIN ANALYSIS            69

FIGURE 21            KEY PLAYERS IN KNOWLEDGE GRAPH MARKET ECOSYSTEM       71

FIGURE 22            LIST OF MAJOR PATENTS FOR KNOWLEDGE GRAPH 77

FIGURE 23            PORTER’S FIVE FORCES MODEL: KNOWLEDGE GRAPH MARKET               91

FIGURE 24            INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE VERTICALS   93

FIGURE 25            KEY BUYING CRITERIA FOR TOP THREE VERTICALS         93

FIGURE 26            EVOLUTION OF KNOWLEDGE GRAPH   94

FIGURE 27            USE CASES OF GENERATIVE AI IN KNOWLEDGE GRAPH 98

FIGURE 28            KNOWLEDGE GRAPH MARKET: INVESTMENT AND FUNDING SCENARIO

(USD MILLION) 99

FIGURE 29            SERVICES SEGMENT TO GROW AT HIGHER CAGR DURING FORECAST PERIOD          107

FIGURE 30            ENTERPRISE KNOWLEDGE GRAPH PLATFORM SEGMENT TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD                108

FIGURE 31            MANAGED SERVICES SEGMENT TO GROW AT HIGHER CAGR DURING

FORECAST PERIOD         113

FIGURE 32            RDF TRIPLE STORES MODEL TYPE TO GROW AT HIGHER CAGR DURING

FORECAST PERIOD         118

FIGURE 33            DATA ANALYTICS & BUSINESS INTELLIGENCE SEGMENT TO ACCOUNT

FOR LARGEST MARKET DURING FORECAST PERIOD      123

FIGURE 34            HEALTHCARE, LIFE SCIENCES, AND PHARMACEUTICALS SEGMENT TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD       137

FIGURE 35            NORTH AMERICA: MARKET SNAPSHOT 183

FIGURE 36            ASIA PACIFIC: MARKET SNAPSHOT          212

FIGURE 37            REVENUE ANALYSIS OF KEY COMPANIES IN PAST 5 YEARS    257

FIGURE 38            SHARE OF LEADING COMPANIES IN KNOWLEDGE GRAPH MARKET, 2024        258

FIGURE 39            MARKET RANKING ANALYSIS OF TOP FIVE PLAYERS              259

FIGURE 40            KNOWLEDGE GRAPH MARKET: COMPANY EVALUATION MATRIX

(KEY PLAYERS), 2024       261

FIGURE 41            KNOWLEDGE GRAPH MARKET: COMPANY FOOTPRINT       262

FIGURE 42            KNOWLEDGE GRAPH MARKET: COMPANY EVALUATION MATRIX

(START-UPS/SMES), 2024               266

FIGURE 43            BRAND/PRODUCT COMPARISON             274

FIGURE 44            FINANCIAL METRICS OF KEY KNOWLEDGE GRAPH MARKET VENDORS         275

FIGURE 45            COMPANY VALUATION OF KEY KNOWLEDGE GRAPH MARKET VENDORS         275

FIGURE 46            AMAZON WEB SERVICES: COMPANY SNAPSHOT                 280

FIGURE 47            IBM: COMPANY SNAPSHOT         291

FIGURE 48            MICROSOFT: COMPANY SNAPSHOT        294

FIGURE 49            SAP: COMPANY SNAPSHOT         298

FIGURE 50            ORACLE: COMPANY SNAPSHOT                301

FIGURE 51            ALTAIR: COMPANY SNAPSHOT 312

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