Knowledge Graph Market

Knowledge Graph Market by Offering (Solutions, Services), By Data Source (Structured, Unstructured, Semi-structured), Industry (BFSI, IT & ITeS, Telecom, Healthcare), Model Type, Application, Type and Region - Global Forecast to 2028

Report Code: TC 8832 Oct, 2023, by marketsandmarkets.com

Knowledge Graph Market Share, Forecast & Growth Analysis

[242 Pages Report] The Knowledge Graph Market size in terms of revenue was reasonably estimated at $0.9 billion in 2023. It is anticipated to grow at a Compound Annual Growth Rate (CAGR) of 21.8%. The revenue forecast for 2028 is set to enjoy a valuation of $2.4 billion. The base year considered for estimation is 2022 and the historical data span from 2023 to 2028.

The increasing volume, velocity, and variety of big data have led to the need for efficient data processing and analysis. Knowledge graphs enable real-time data processing, helping organizations make quick, data-driven decisions based on the most up-to-date information available. Also, with advancements in NLP, there is a growing need for more sophisticated data models that can understand and process human language effectively. Knowledge graphs play a crucial role in enhancing NLP capabilities by enabling machines to comprehend the context and relationships between words and phrases.

Knowledge Graph Market

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Knowledge Graph Market

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Knowledge Graph Market Growth Dynamics

Driver:  AI and ML to drive market growth

The explosion of data generated by businesses and individuals, combined with advanced AI (Artificial Intelligence) and ML (Machine Learning) algorithms, has become the cornerstone of knowledge graph applications. Furthermore, the availability of high-performance computing resources and the prevalence of cloud computing platforms have made it easier to process vast amounts of data and deploy complex AI models. The Internet of Things (IoT) has added to this momentum, as AI/ML enables the extraction of valuable insights from IoT data to enrich knowledge graphs. Additionally, Natural Language Processing (NLP) technologies have improved the ability to understand and extract information from textual data, enhancing knowledge graph construction. Across various industries, AI and ML are being adopted to automate tasks, ensure regulatory compliance, and create personalized experiences, all contributing to market growth. Moreover, the recent pandemic accelerated digital transformation efforts, emphasizing the need for AI and ML solutions in knowledge graph applications to meet evolving user expectations.

Restraint: Cost of development and maintenance

The cost of developing and maintaining a knowledge graph for the market can vary significantly based on several factors such as complexity of the domain, the scale of the knowledge graph, the technology stack used, and the ongoing maintenance requirements. The scope and complexity of the knowledge graph plays a pivotal role, more extensive and intricate graphs tend to incur higher development costs. Data acquisition is another cost consideration, as obtaining high-quality data sources may require purchasing data or developing data collection tools. The choice of technology stack, including licensing fees and operational costs for cloud-based solutions, can impact expenses. Skilled development teams, ontology and schema design, and ongoing maintenance all contribute to the overall cost. Scalability, security, and compliance requirements further add to expenses.

Opportunity: NLP to boost knowledge graph market

The integration of Natural Language Processing (NLP) techniques into the knowledge graph market presents a wealth of opportunities for data enrichment and enhanced user experiences. NLP enables the extraction of entities, relations, and facts from unstructured text data, enriching the knowledge graph with valuable information. It allows for sentiment analysis, contextual understanding, and the ability to process natural language queries, making knowledge graphs more accessible and user-friendly. NLP can also improve data quality, aid in personalization, and facilitate trend analysis. Overall, the synergy between NLP and knowledge graphs empowers organizations to unlock deeper insights from their data, promote efficient data integration, and provide more meaningful interactions with their knowledge graph-based systems across various domains.

Challenge: Data quality and integration

Data quality and integration are indeed significant challenges when it comes to building and maintaining knowledge graphs. Achieving the full potential of knowledge graphs relies on the accuracy and reliability of the underlying data. Inaccuracies and inconsistencies can lead to erroneous insights, emphasizing the need for rigorous data quality measures. Furthermore, integrating diverse data sources, each with their own formats and structures, requires intricate schema mapping and transformation processes. Semantic interoperability and entity resolution are additional hurdles to overcome to ensure meaningful connections within the knowledge graph. Scalability, performance optimization, and adherence to data security and privacy standards are crucial for sustained success.

Knowledge graph market Ecosystem

Prominent companies in this market include a well-established, financially stable provider of the knowledge graph market. These companies have innovated their offerings and possess a diversified product portfolio, state-of-the-art technologies, and marketing networks. Prominent companies in this market include IBM (US), Microsoft (US), AWS (US), Neo4j (US), TigerGraph (US), SAP (Germany), Oracle (US), Stardog (US), Franz Inc (US), Ontotext (Bulgaria).

Knowledge Graph Market

By data source, the structured data segment is expected to grow with the highest CAGR during the forecast period

Integrating structured data sources within the knowledge graph market fundamentally transforms how businesses process and utilize information. By seamlessly merging various data repositories, such as databases and organized datasets, into the knowledge graph framework, companies can now establish a comprehensive understanding of complex relationships and interconnections between different entities. This integration also facilitates the semantic enrichment of the knowledge graph, imbuing it with contextual depth and meaning. Additionally, structured data sources aid in efficient entity resolution, ensuring data accuracy and consistency by identifying and consolidating similar entities. Moreover, the utilization of structured data serves as the backbone for creating a structured knowledge representation within the knowledge graph, enabling businesses to grasp intricate knowledge domains and make informed decisions based on reliable insights.

By vertical, the BFSI segment to hold the largest market size during the forecast period

In recent years, the Banking, Financial Services, and Insurance (BFSI) sector has increasingly embraced the transformative power of knowledge graphs. These sophisticated tools have proven instrumental in managing the complex web of data inherent in the industry. By integrating disparate data sources, organizations can comprehensively understand their operations and customer interactions. Furthermore, knowledge graphs are vital in risk management and compliance, enabling institutions to identify, assess, and mitigate various risks while ensuring adherence to regulatory standards. In fraud detection and prevention, these graphs excel at identifying anomalies and suspicious patterns in real-time. With data security and privacy becoming increasingly critical, knowledge graphs play a crucial role in enhancing data security measures and privacy controls.

Based on region, North America hold the largest market size during the forecast period

The knowledge graph market in North America has been experiencing significant growth and development. Large enterprises across various sectors have been actively adopting knowledge graphs to enhance data integration, knowledge management, and decision-making processes. Increased investment and innovation have fueled the advancement of knowledge graph technologies, making them more adaptable and scalable to different industries and use cases. Integration with AI and machine learning has enabled more sophisticated data analysis and predictive modeling, leading to better-informed decision-making and improved operational efficiencies. Data governance and compliance have also been key focus areas, with knowledge graphs aiding in ensuring data quality, integrity, and security.

Knowledge Graph Market Size, and Share

Market Players:

The major players in the Knowledge graph market are IBM (US), Microsoft (US), AWS (US), SAP (US), Neo4j (US), and Oracle (US). These players have adopted various growth strategies, such as partnerships, agreements and collaborations, new product launches, product enhancements, and acquisitions to expand their footprint in the knowledge graph market.

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Scope of the Report

Report Metrics

Details

Market size available for years

2018-2028

Base year considered

2022

Forecast period

2023–2028

Forecast units

Value (USD) Million/Billion

Segments Covered

Offering (Solutions and Services), Model Type (RDF Graph, Conceptual Graph, and Semantic Graph), Data Source (Structured Data, Unstructured Data, and Semi-structured Data), Application (Semantic Search, Question Answering, Recommendation Systems, Enterprise Knowledge Management, Other Applications), Type (Context-rich Knowledge Graphs, External-sensing Knowledge Graphs, NLP Knowledge Graphs), Vertical, and Region

Region covered

North America, Europe, Asia Pacific, Middle East & Africa, Latin America

Companies covered

IBM (US), Microsoft (US), AWS (US), Neo4j (US), TigerGraph (US), SAP (Germany), Oracle (US), Stardog (US), Franz Inc (US), Ontotext (Bulgaria), Semantic Web Company (Austria), OpenLink Software (US), MarkLogic (US), Datavid (UK), GraphBase (Australia), Cambridge Semantics (US), CoverSight (US), Eccena Gmbh (Germany), ArangoDB (US), Fluree (US), DiffBot (US), Bitnine (US), Memgraph (England), GraphAware (UK), Onlim (Austria)

This research report categorizes the knowledge graph market based on offering, model type, data source, application, type, vertical, and region.

Based on the Offering:
  • Solutions
  • Services
    • Professional Services
    • Managed Services
Based on the Model Type:
  • RDF Graph
  • Conceptual Graph
  • Semantic Graph
Based on Data Source
  • Structured Data
  • Unstructured Data
  • Semi-structured Data
Based on the Application:
  • Semantic Search
  • Question Answering
  • Recommendation Systems
  • Enterprise Knowledge Management
  • Other Applications
Based on the Type:
  • Context-rich Knowledge Graphs
  • External-sensing Knowledge Graphs
  • NLP Knowledge Graphs
Based on the Vertical:
  • BFSI
  • IT & ITES
  • Retail and E-commerce
  • Travel and Hospitality
  • Healthcare
  • Media and Entertainment
  • Transportation and Logistics
  • Other Verticals
Based on the region:
  • North America
    • US
    • Canada
  • Europe
    • UK
    • Germany
    • France
    • Spain
    • Italy
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • Australia and New Zealand (ANZ)
    • Rest of Asia Pacific
  • Middle East & Africa
    • GCC
    • South Africa
    • Rest of Middle East & Africa
  • Latin America
    • Brazil
    • Mexico
    • Rest of Latin America

Recent Developments

  • In February 2023, IBM acquired StepZen, which developed a GraphQL server with a unique architecture that helps developers build GraphQL APIs quickly and with less code. StepZen was also designed to be highly flexible. It is compatible with other API approaches and is available Software-as-a-Service (SaaS) while supporting deployments in private clouds and on-premises data centers.
  • In May 2023, AWS partnered with Neo4j , which defined the graph space and open-source standards. Neo4j holds the AWS Data and Analytics Competency.
  • In April 2023, Neo4j announced a partnership with Imperium Solutions to fulfill the growing demand for graph technology in Singapore. Imperium Solutions will ensure customers can gain maximum value from the world’s leading graph database provider, Neo4j, which helps solve complex, enterprise-level problems and efficiently uncovers relationships and patterns in expansive datasets.
  • In May 2023, Accenture has made a strategic investment through Accenture Ventures in Stardog, a leading enterprise knowledge graph platform enabling organizations to do more with and achieve greater value from their data in this age of generative artificial intelligence (AI). Stardog Enterprise Knowledge Graphs, with their ability to make real-world context machine-understandable, are used by companies to facilitate better enterprise data integration and unification. Instead of integrating data by combining tables, data is unified using a knowledge graph’s ability to endlessly link concepts without changing the underlying data.

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TABLE OF CONTENTS
 
1 INTRODUCTION (Page No. - 38)
    1.1 STUDY OBJECTIVES 
    1.2 MARKET DEFINITION 
           1.2.1 INCLUSIONS AND EXCLUSIONS
    1.3 MARKET SCOPE 
           1.3.1 MARKET SEGMENTATION
           1.3.2 REGIONS COVERED
           1.3.3 YEARS CONSIDERED
    1.4 CURRENCY CONSIDERED 
           TABLE 1 USD EXCHANGE RATES, 2020–2022
    1.5 STAKEHOLDERS 
    1.6 RECESSION IMPACT 
 
2 RESEARCH METHODOLOGY (Page No. - 42)
    2.1 RESEARCH DATA 
           FIGURE 1 KNOWLEDGE GRAPH MARKET: RESEARCH DESIGN
           2.1.1 SECONDARY DATA
           2.1.2 PRIMARY DATA
                    2.1.2.1 Breakdown of primaries
                               TABLE 2 PRIMARY INTERVIEWS
                    2.1.2.2 Key industry insights
    2.2 DATA TRIANGULATION 
           FIGURE 2 DATA TRIANGULATION
    2.3 MARKET SIZE ESTIMATION 
           FIGURE 3 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 1 (SUPPLY-SIDE): REVENUE OF OFFERINGS IN KNOWLEDGE GRAPH MARKET
           FIGURE 4 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 2 (DEMAND-SIDE):  MARKET
           2.3.1 BOTTOM-UP APPROACH
                    FIGURE 5 BOTTOM-UP APPROACH
                    FIGURE 6 MARKET SIZE ESTIMATION USING BOTTOM-UP APPROACH
           2.3.2 TOP-DOWN APPROACH
                    FIGURE 7 TOP-DOWN APPROACH
    2.4 MARKET FORECAST 
           TABLE 3 FACTOR ANALYSIS
    2.5 RESEARCH ASSUMPTIONS 
    2.6 LIMITATIONS 
    2.7 IMPACT OF RECESSION ON MARKET 
 
3 EXECUTIVE SUMMARY (Page No. - 52)
    FIGURE 8 KNOWLEDGE GRAPH MARKET, 2021–2028 (USD MILLION) 
    FIGURE 9 MARKET: REGIONAL SHARE, 2023 
    FIGURE 10 ASIA PACIFIC EXPECTED TO BE BEST MARKET FOR INVESTMENTS DURING FORECAST PERIOD 
 
4 PREMIUM INSIGHTS (Page No. - 55)
    4.1 BRIEF OVERVIEW OF KNOWLEDGE GRAPH MARKET 
           FIGURE 11 USE OF NATURAL LANGUAGE PROCESSING IN KNOWLEDGE GRAPHS TO ACT AS OPPORTUNITY IN MARKET
    4.2 NORTH AMERICA: MARKET, BY OFFERING AND TOP THREE VERTICALS 
           FIGURE 12 SOLUTIONS AND BFSI TO ACCOUNT FOR SIGNIFICANT SHARES OF MARKET IN NORTH AMERICA
    4.3 ASIA PACIFIC: MARKET, BY OFFERING AND  TOP THREE COUNTRIES 
           FIGURE 13 SOLUTIONS AND CHINA TO ACCOUNT FOR SIGNIFICANT SHARES OF ASIA PACIFIC MARKET
    4.4 MARKET, BY TYPE 
           FIGURE 14 CONTENT-RICH KNOWLEDGE GRAPHS TO HOLD LARGER MARKET  SHARE IN 2023
    4.5 MARKET, BY APPLICATION 
           FIGURE 15 SEMANTIC SEARCH SEGMENT TO HOLD LARGER MARKET SHARE IN 2023
    4.6 MARKET, BY DATA SOURCE 
           FIGURE 16 UNSTRUCTURED DATA SEGMENT TO HOLD LARGER MARKET SHARE IN 2023
    4.7 KNOWLEDGE GRAPH MARKET, BY MODEL TYPE 
           FIGURE 17 SEMANTIC GRAPH SEGMENT TO HOLD LARGER MARKET SHARE IN 2023
 
5 MARKET OVERVIEW AND INDUSTRY TRENDS (Page No. - 58)
    5.1 MARKET OVERVIEW 
    5.2 MARKET DYNAMICS 
           FIGURE 18 DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES: MARKET
           5.2.1 DRIVERS
                    5.2.1.1 Rapid growth in data volume and complexity
                    5.2.1.2 Advanced AI & ML algorithms and vast amount of generated data
                    5.2.1.3 Semantic web and linked data initiatives
           5.2.2 RESTRAINTS
                    5.2.2.1 Significant costs for development and maintenance
           5.2.3 OPPORTUNITIES
                    5.2.3.1 Integration of NLP techniques into knowledge graph market to help data enrichment and enhance user experiences
                    5.2.3.2 Increasing adoption in healthcare and life sciences
           5.2.4 CHALLENGES
                    5.2.4.1 Data quality and integration
                    5.2.4.2 Scalability
    5.3 INDUSTRY TRENDS 
    5.4 REGULATORY IMPLICATIONS 
           5.4.1 GENERAL DATA PROTECTION REGULATION
           5.4.2 INTERNATIONAL ORGANIZATION FOR STANDARDIZATION 27001
           5.4.3 EU DATA GOVERNANCE ACT
           5.4.4 HEALTH INSURANCE PORTABILITY AND ACCOUNTABILITY  ACT OF 1996
           5.4.5 BASEL COMMITTEE ON BANKING SUPERVISION 239 COMPLIANCE
           5.4.6 SARBANES-OXLEY ACT OF 2002
    5.5 BEST PRACTICES IN KNOWLEDGE GRAPH MARKET 
           5.5.1 VALUE CHAIN ANALYSIS
                    FIGURE 19 MARKET: VALUE CHAIN ANALYSIS
           5.5.2 BRIEF HISTORY OF MARKET
                    FIGURE 20 BRIEF HISTORY OF KNOWLEDGE GRAPH
                    5.5.2.1 2000–2010
                    5.5.2.2 2010–2020
                    5.5.2.3 2020–Present
           5.5.3 ECOSYSTEM
                    FIGURE 21 KNOWLEDGE GRAPH ECOSYSTEM
                    TABLE 4 KNOWLEDGE GRAPH MARKET: ECOSYSTEM
           5.5.4 PATENT ANALYSIS
                    5.5.4.1 Methodology
                    5.5.4.2 Document type
                               TABLE 5 PATENTS FILED, 2020–2023
                    5.5.4.3 Innovation and patent applications
                               FIGURE 22 TOTAL NUMBER OF PATENTS GRANTED, 2020–2023
                    5.5.4.4 Top applicants
                               FIGURE 23 TOP TEN PATENT APPLICANTS, 2020–2023
           5.5.5 USE CASES
                    TABLE 6 KERBEROS PREVENTED MONEY LAUNDERING AND DEVELOPED COMPLIANCE MANAGEMENT APPLICATION FOR RISK MANAGEMENT WITH NEO4J
                    TABLE 7 YAHOO7 REPRESENTED CONTENT WITHIN KNOWLEDGE GRAPH WITH ASSISTANCE OF BLAZEGRAPH
                    TABLE 8 NEO4J ENABLED AND VISUALIZED CONNECTIONS BETWEEN ELEMENTS OF PANAMA PAPERS LEAKS
                    TABLE 9 GRAPH TECHNOLOGY HELPED US ARMY BY TRACKING AND ANALYZING EQUIPMENT MAINTENANCE AFTER EMPLOYING NEO4J
                    TABLE 10 THE DATABASE GROUP HELPED SPRINGERMATERIALS ACCELERATE RESEARCH WITH SEMANTIC SEARCH
           5.5.6 PRICING ANALYSIS
                    5.5.6.1 Average selling price of key players
                               TABLE 11 PRICING ANALYSIS
                    5.5.6.2 Average selling price trends
    5.6 IMPACT OF KNOWLEDGE GRAPH ON ADJACENT TECHNOLOGIES 
           5.6.1 TECHNOLOGY ANALYSIS
                    5.6.1.1 Adjacent technologies
                               5.6.1.1.1 NLP
                               5.6.1.1.2 Big data & analytics
                               5.6.1.1.3 Graph neural networks
                    5.6.1.2 Related technologies
                               5.6.1.2.1 Cloud computing
                               5.6.1.2.2 AI and ML
                               5.6.1.2.3 IoT
                               5.6.1.2.4 Blockchain
           5.6.2 PORTER’S FIVE FORCES ANALYSIS
                    TABLE 12 KNOWLEDGE GRAPH MARKET: PORTER’S FIVE FORCES MODEL
                    5.6.2.1 Threat of new entrants
                    5.6.2.2 Threat of substitutes
                    5.6.2.3 Bargaining power of buyers
                    5.6.2.4 Bargaining power of suppliers
                    5.6.2.5 Intensity of competitive rivalry
           5.6.3 DISRUPTIONS IMPACTING BUYERS/CUSTOMERS IN MARKET
                    FIGURE 24 TRENDS/DISRUPTIONS IMPACTING BUYERS/CUSTOMERS IN MARKET
           5.6.4 KEY CONFERENCES & EVENTS IN 2023–2024
                    TABLE 13 KNOWLEDGE GRAPH MARKET: DETAILED LIST OF CONFERENCES & EVENTS
           5.6.5 KEY STAKEHOLDERS & BUYING CRITERIA
                    5.6.5.1 Key stakeholders in buying process
                               FIGURE 25 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE END-USE INDUSTRIES
                               TABLE 14 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE END-USE INDUSTRIES (%)
                    5.6.5.2 Buying criteria
                               FIGURE 26 KEY BUYING CRITERIA FOR TOP THREE END-USE INDUSTRIES
                               TABLE 15 KEY BUYING CRITERIA FOR TOP THREE END-USE INDUSTRIES
           5.6.6 STEPS TO BUILD KNOWLEDGE GRAPH
                    5.6.6.1 Identify domain
                    5.6.6.2 Define entities
                    5.6.6.3 Define relationships
                    5.6.6.4 Determine attributes
                    5.6.6.5 Model graph
                    5.6.6.6 Map data
                    5.6.6.7 Validate model
                    5.6.6.8 Refine model
           5.6.7 FUTURE DIRECTION OF MARKET
 
6 KNOWLEDGE GRAPH MARKET, BY OFFERING (Page No. - 83)
    6.1 INTRODUCTION 
           6.1.1 OFFERING: MARKET DRIVERS
                    FIGURE 27 SERVICES SEGMENT TO GROW AT HIGHER CAGR DURING FORECAST PERIOD
                    TABLE 16 MARKET, BY OFFERING, 2018–2022 (USD MILLION)
                    TABLE 17 MARKET, BY OFFERING, 2023–2028 (USD MILLION)
    6.2 SOLUTIONS 
           6.2.1 SPIKE IN DEMAND FOR SOPHISTICATED DATA MANAGEMENT AND ANALYSIS TO DRIVE MARKET
                    TABLE 18 SOLUTIONS: MARKET, BY REGION, 2018–2022 (USD MILLION)
                    TABLE 19 SOLUTIONS: MARKET, BY REGION, 2023–2028 (USD MILLION)
    6.3 SERVICES 
           6.3.1 GROWING NEED TO IMPROVE EFFICIENCY TO BOOST MARKET
                    TABLE 20 SERVICES: MARKET, BY REGION, 2018–2022 (USD MILLION)
                    TABLE 21 SERVICES: MARKET, BY REGION, 2023–2028 (USD MILLION)
           6.3.2 MANAGED SERVICES
           6.3.3 PROFESSIONAL SERVICES
 
7 MARKET, BY MODEL TYPE (Page No. - 88)
    7.1 INTRODUCTION 
           7.1.1 MODEL TYPE: KNOWLEDGE GRAPH MARKET DRIVERS
                    FIGURE 28 CONCEPTUAL GRAPHS TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
                    TABLE 22 MARKET, BY MODEL TYPE, 2018–2022 (USD MILLION)
                    TABLE 23 MARKET, BY MODEL TYPE, 2023–2028 (USD MILLION)
    7.2 RDF GRAPHS 
           7.2.1 NEED TO ADOPT INTELLIGENT DATA MANAGEMENT SOLUTIONS TO DRIVE MARKET
                    TABLE 24 RDF GRAPHS: MARKET, BY REGION, 2018–2022 (USD MILLION)
                    TABLE 25 RDF GRAPHS: MARKET, BY REGION, 2023–2028 (USD MILLION)
    7.3 CONCEPTUAL GRAPHS 
           7.3.1 LOGICAL INFERENCE, KNOWLEDGE DISCOVERY, AND STRUCTURED REPRESENTATION OF DATA TO PROPEL MARKET GROWTH
                    TABLE 26 CONCEPTUAL GRAPHS: MARKET, BY REGION,  2018–2022 (USD MILLION)
                    TABLE 27 CONCEPTUAL GRAPHS: MARKET, BY REGION,  2023–2028 (USD MILLION)
    7.4 SEMANTIC GRAPHS 
           7.4.1 SEAMLESS INTEGRATION OF DISPARATE DATA SOURCES TO FUEL MARKET GROWTH
                    TABLE 28 SEMANTIC GRAPHS: MARKET, BY REGION,  2018–2022 (USD MILLION)
                    TABLE 29 SEMANTIC GRAPHS: MARKET, BY REGION,  2023–2028 (USD MILLION)
 
8 MARKET, BY DATA SOURCE (Page No. - 94)
    8.1 INTRODUCTION 
           8.1.1 DATA SOURCE: KNOWLEDGE GRAPH MARKET DRIVERS
                    FIGURE 29 STRUCTURED DATA PROJECTED TO GROW AT HIGHEST CAGR DURING  FORECAST PERIOD
                    TABLE 30 MARKET, BY DATA SOURCE, 2018–2022 (USD MILLION)
                    TABLE 31 MARKET, BY DATA SOURCE, 2023–2028 (USD MILLION)
    8.2 STRUCTURED DATA 
           8.2.1 GROWING NEED FOR DATA ACCURACY AND CONSISTENCY TO ACCELERATE MARKET GROWTH
                    TABLE 32 STRUCTURED DATA: MARKET, BY REGION,  2018–2022 (USD MILLION)
                    TABLE 33 STRUCTURED DATA: MARKET, BY REGION,  2023–2028 (USD MILLION)
    8.3 UNSTRUCTURED DATA 
           8.3.1 INCREASING FOCUS ON UNSTRUCTURED DATA SOURCES TO BOOST RESEARCH IN DATA ENRICHMENT AND CONTEXTUAL UNDERSTANDING
                    TABLE 34 UNSTRUCTURED DATA: MARKET, BY REGION,  2018–2022 (USD MILLION)
                    TABLE 35 UNSTRUCTURED DATA: MARKET, BY REGION,  2023–2028 (USD MILLION)
    8.4 SEMI-STRUCTURED DATA 
           8.4.1 SEMI-STRUCTURED DATA SOURCES TO ASSIST ENTERPRISES IN PERCEPTIVE DEPICTION OF INTRICATE INFORMATION
                    TABLE 36 SEMI-STRUCTURED DATA: MARKET, BY REGION,  2018–2022 (USD MILLION)
                    TABLE 37 SEMI-STRUCTURED DATA: MARKET, BY REGION,  2023–2028 (USD MILLION)
 
9 KNOWLEDGE GRAPH MARKET, BY APPLICATION (Page No. - 100)
    9.1 INTRODUCTION 
           9.1.1 APPLICATION: MARKET DRIVERS
                    FIGURE 30 SEMANTIC SEARCH EXPECTED TO ACCOUNT FOR LARGEST MARKET IN 2028
                    TABLE 38 MARKET, BY APPLICATION, 2018–2022 (USD MILLION)
                    TABLE 39 MARKET, BY APPLICATION, 2023–2028 (USD MILLION)
    9.2 SEMANTIC SEARCH 
           9.2.1 NEED FOR ENHANCED SEARCH FUNCTIONALITIES TO DRIVE THE MARKET
                    TABLE 40 SEMANTIC SEARCH: MARKET, BY REGION,  2018–2022 (USD MILLION)
                    TABLE 41 SEMANTIC SEARCH: MARKET, BY REGION,  2023–2028 (USD MILLION)
    9.3 QUESTION ANSWERING 
           9.3.1 INTEGRATION OF KNOWLEDGE FROM SEVERAL DISCIPLINES AND OFFERING PERSONALIZED RECOMMENDATIONS TO DRIVE MARKET
                    TABLE 42 QUESTION ANSWERING: MARKET, BY REGION,  2018–2022 (USD MILLION)
                    TABLE 43 QUESTION ANSWERING: KNOWLEDGE GRAPH MARKET, BY REGION,  2023–2028 (USD MILLION)
    9.4 RECOMMENDATION SYSTEMS 
           9.4.1 WIDESPREAD KNOWLEDGE OF INTRICATE IDEAS THROUGH CROSS-DOMAIN INFORMATION INTEGRATION TO BOOST MARKET
                    TABLE 44 RECOMMENDATION SYSTEMS: MARKET, BY REGION, 2018–2022 (USD MILLION)
                    TABLE 45 RECOMMENDATION SYSTEMS: MARKET, BY REGION,  2023–2028 (USD MILLION)
    9.5 ENTERPRISE KNOWLEDGE MANAGEMENT 
           9.5.1 STREAMLINING OF TEAMWORK AND KNOWLEDGE EXCHANGE TO ACCELERATE MARKET GROWTH
                    TABLE 46 ENTERPRISE KNOWLEDGE MANAGEMENT: MARKET, BY REGION, 2018–2022 (USD MILLION)
                    TABLE 47 ENTERPRISE KNOWLEDGE MANAGEMENT: MARKET, BY REGION, 2023–2028 (USD MILLION)
    9.6 OTHER APPLICATIONS 
           TABLE 48 OTHER APPLICATIONS: MARKET, BY REGION,  2018–2022 (USD MILLION)
           TABLE 49 OTHER APPLICATIONS: MARKET, BY REGION,  2023–2028 (USD MILLION)
 
10 KNOWLEDGE GRAPH MARKET, BY TYPE (Page No. - 108)
     10.1 INTRODUCTION 
             10.1.1 TYPE: MARKET DRIVERS
                       FIGURE 31 NLP GRAPHS EXPECTED TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
                       TABLE 50 MARKET, BY TYPE, 2018–2022 (USD MILLION)
                       TABLE 51 MARKET, BY TYPE, 2023–2028 (USD MILLION)
     10.2 CONTEXT-RICH KNOWLEDGE GRAPHS 
             10.2.1 CONTEXT-RICH KNOWLEDGE GRAPHS TO HELP ORGANIZATIONS ACHIEVE OPERATIONAL EXCELLENCE AND COMPETITIVE ADVANTAGE
                       TABLE 52 CONTEXT-RICH KNOWLEDGE GRAPHS: MARKET, BY REGION,  2018–2022 (USD MILLION)
                       TABLE 53 CONTEXT-RICH KNOWLEDGE GRAPHS: MARKET, BY REGION,  2023–2028 (USD MILLION)
     10.3 EXTERNAL-SENSING KNOWLEDGE GRAPHS 
             10.3.1 REAL-TIME UPDATES FROM EXTERNAL-SENSING KNOWLEDGE GRAPHS TO FOSTER FLEXIBILITY AND AGILITY
                       TABLE 54 EXTERNAL-SENSING KNOWLEDGE GRAPHS: MARKET, BY REGION, 2018–2022 (USD MILLION)
                       TABLE 55 EXTERNAL-SENSING KNOWLEDGE GRAPHS: MARKET, BY REGION, 2023–2028 (USD MILLION)
     10.4 NLP KNOWLEDGE GRAPHS 
             10.4.1 KNOWLEDGE DISCOVERY AND DATA INTEGRATION TO FUEL MARKET GROWTH
                       TABLE 56 NLP KNOWLEDGE GRAPHS: MARKET, BY REGION,  2018–2022 (USD MILLION)
                       TABLE 57 NLP KNOWLEDGE GRAPHS: MARKET, BY REGION,  2023–2028 (USD MILLION)
 
11 KNOWLEDGE GRAPH MARKET, BY VERTICAL (Page No. - 114)
     11.1 INTRODUCTION 
             11.1.1 VERTICAL: MARKET DRIVERS
                       FIGURE 32 IT & ITES TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
                       TABLE 58 MARKET, BY VERTICAL, 2018–2022 (USD MILLION)
                       TABLE 59 MARKET, BY VERTICAL, 2023–2028 (USD MILLION)
     11.2 BFSI 
             11.2.1 INCREASING NEED TO MANAGE COMPLEX DATA TO SUPPORT MARKET GROWTH
                       TABLE 60 BFSI: MARKET, BY REGION, 2018–2022 (USD MILLION)
                       TABLE 61 BFSI: MARKET, BY REGION, 2023–2028 (USD MILLION)
             11.2.2 CASE STUDY
                       11.2.2.1 Prominent financial institution was able to combat money laundering with TigerGraph
     11.3 RETAIL & ECOMMERCE 
             11.3.1 OPTIMIZED INVENTORY MANAGEMENT FACILITATED BY KNOWLEDGE GRAPHS TO DRIVE MARKET
                       TABLE 62 RETAIL & ECOMMERCE: MARKET, BY REGION,  2018–2022 (USD MILLION)
                       TABLE 63 RETAIL & ECOMMERCE: MARKET, BY REGION,  2023–2028 (USD MILLION)
             11.3.2 CASE STUDY
                       11.3.2.1 Retailer improved store operations and increased customer satisfaction using TigerGraph
     11.4 MANUFACTURING & AUTOMOTIVE 
             11.4.1 EASY PREDICTIVE MAINTENANCE AND DECREASE IN DOWNTIME TO SUPPORT MARKET GROWTH
                       TABLE 64 MANUFACTURING & AUTOMOTIVE: KNOWLEDGE GRAPH MARKET, BY REGION,  2018–2022 (USD MILLION)
                       TABLE 65 MANUFACTURING & AUTOMOTIVE: MARKET, BY REGION,  2023–2028 (USD MILLION)
             11.4.2 CASE STUDY
                       11.4.2.1 Leading building automation systems (BAS) manufacturers used Brick schema to represent BAS components and their complex interactions
     11.5 IT & ITES 
             11.5.1 DEVELOPMENT OF INNOVATIVE TECHNOLOGIES TO DRIVE MARKET
                       TABLE 66 IT & ITES: MARKET, BY REGION, 2018–2022 (USD MILLION)
                       TABLE 67 IT & ITES: MARKET, BY REGION, 2023–2028 (USD MILLION)
             11.5.2 CASE STUDY
                       11.5.2.1 Technology giant improved customer experiences with TigerGraph
     11.6 TELECOM 
             11.6.1 OPTIMIZED INTRICATE NETWORK INFRASTRUCTURE AND CUSTOMIZED SERVICE OFFERINGS TO FUEL MARKET GROWTH
                       TABLE 68 TELECOM: MARKET, BY REGION, 2018–2022 (USD MILLION)
                       TABLE 69 TELECOM: MARKET, BY REGION, 2023–2028 (USD MILLION)
             11.6.2 CASE STUDY
                       11.6.2.1 Orange used Thing’in to build digital twin platform
     11.7 MEDIA & ENTERTAINMENT 
             11.7.1 IMPROVED CONTENT MANAGEMENT PROCEDURES AND BETTER DATA-DRIVEN DECISIONS TO BOOST MARKET
                       TABLE 70 MEDIA & ENTERTAINMENT: MARKET, BY REGION,  2018–2022 (USD MILLION)
                       TABLE 71 MEDIA & ENTERTAINMENT: MARKET, BY REGION,  2023–2028 (USD MILLION)
             11.7.2 CASE STUDY
                       11.7.2.1 Perfect Memory and Ontotext developed custom data program platform based on knowledge graph solution to streamline data management
     11.8 HEALTHCARE 
             11.8.1 NEED TO REVOLUTIONIZE HEALTHCARE PRACTICES TO PROPEL ADOPTION OF KNOWLEDGE GRAPHS
                       TABLE 72 HEALTHCARE: KNOWLEDGE GRAPH MARKET, BY REGION, 2018–2022 (USD MILLION)
                       TABLE 73 HEALTHCARE: MARKET, BY REGION, 2023–2028 (USD MILLION)
             11.8.2 CASE STUDY
                       11.8.2.1 Amgen improved quality of healthcare by identifying influencers and referral networks using TigerGraph
     11.9 GOVERNMENT 
             11.9.1 SPEEDY DATA INTEGRATION AND INTEROPERABILITY TO BOOST MARKET
                       TABLE 74 GOVERNMENT: MARKET, BY REGION, 2018–2022 (USD MILLION)
                       TABLE 75 GOVERNMENT: MARKET, BY REGION, 2023–2028 (USD MILLION)
             11.9.2 CASE STUDY
                       11.9.2.1 State Grid Corporation of China created speedy energy management system with assistance of TigerGraph
     11.10 OTHER VERTICALS 
               TABLE 76 OTHER VERTICALS: MARKET, BY REGION,  2018–2022 (USD MILLION)
               TABLE 77 OTHER VERTICALS: MARKET, BY REGION,  2023–2028 (USD MILLION)
 
12 KNOWLEDGE GRAPH MARKET, BY REGION (Page No. - 128)
     12.1 INTRODUCTION 
               FIGURE 33 MARKET: REGIONAL SNAPSHOT, 2023
               FIGURE 34 ASIA PACIFIC TO ACCOUNT FOR HIGHEST CAGR DURING FORECAST PERIOD
               TABLE 78 MARKET, BY REGION, 2018–2022 (USD MILLION)
               TABLE 79 MARKET, BY REGION, 2023–2028 (USD MILLION)
     12.2 NORTH AMERICA 
               FIGURE 35 NORTH AMERICA: MARKET SNAPSHOT
             12.2.1 NORTH AMERICA: MARKET DRIVERS
             12.2.2 NORTH AMERICA: RECESSION IMPACT
                       TABLE 80 NORTH AMERICA: KNOWLEDGE GRAPH MARKET, BY OFFERING,  2018–2022 (USD MILLION)
                       TABLE 81 NORTH AMERICA: MARKET, BY OFFERING,  2023–2028 (USD MILLION)
                       TABLE 82 NORTH AMERICA: MARKET, BY TYPE,  2018–2022 (USD MILLION)
                       TABLE 83 NORTH AMERICA: MARKET, BY TYPE,  2023–2028 (USD MILLION)
                       TABLE 84 NORTH AMERICA: MARKET, BY DATA SOURCE,  2018–2022 (USD MILLION)
                       TABLE 85 NORTH AMERICA: MARKET, BY DATA SOURCE,  2023–2028 (USD MILLION)
                       TABLE 86 NORTH AMERICA: MARKET, BY MODEL TYPE,  2018–2022 (USD MILLION)
                       TABLE 87 NORTH AMERICA: MARKET, BY MODEL TYPE,  2023–2028 (USD MILLION)
                       TABLE 88 NORTH AMERICA: MARKET, BY APPLICATION,  2018–2022 (USD MILLION)
                       TABLE 89 NORTH AMERICA: MARKET, BY APPLICATION,  2023–2028 (USD MILLION)
                       TABLE 90 NORTH AMERICA: MARKET, BY VERTICAL,  2018–2022 (USD MILLION)
                       TABLE 91 NORTH AMERICA: MARKET, BY VERTICAL,  2023–2028 (USD MILLION)
                       TABLE 92 NORTH AMERICA: MARKET, BY COUNTRY,  2018–2022 (USD MILLION)
                       TABLE 93 NORTH AMERICA: MARKET, BY COUNTRY,  2023–2028 (USD MILLION)
             12.2.3 US
                       12.2.3.1 Spike in demand for advanced solutions and data-driven adoption initiatives to drive market
                                   TABLE 94 US: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2018–2022 (USD MILLION)
                                   TABLE 95 US: MARKET, BY OFFERING, 2023–2028 (USD MILLION)
                                   TABLE 96 US: MARKET, BY TYPE, 2018–2022 (USD MILLION)
                                   TABLE 97 US: MARKET, BY TYPE, 2023–2028 (USD MILLION)
                                   TABLE 98 US: MARKET, BY DATA SOURCE, 2018–2022 (USD MILLION)
                                   TABLE 99 US: MARKET, BY DATA SOURCE, 2023–2028 (USD MILLION)
                                   TABLE 100 US: MARKET, BY MODEL TYPE, 2018–2022 (USD MILLION)
                                   TABLE 101 US: MARKET, BY MODEL TYPE, 2023–2028 (USD MILLION)
                                   TABLE 102 US: MARKET, BY APPLICATION, 2018–2022 (USD MILLION)
                                   TABLE 103 US: MARKET, BY APPLICATION, 2023–2028 (USD MILLION)
                                   TABLE 104 US: MARKET, BY VERTICAL, 2018–2022 (USD MILLION)
                                   TABLE 105 US: MARKET, BY VERTICAL, 2023–2028 (USD MILLION)
             12.2.4 CANADA
                       12.2.4.1 Need for real-time decision-making to drive market
     12.3 EUROPE 
             12.3.1 EUROPE: MARKET DRIVERS
             12.3.2 EUROPE: RECESSION IMPACT
                       TABLE 106 EUROPE: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2018–2022 (USD MILLION)
                       TABLE 107 EUROPE: MARKET, BY OFFERING, 2023–2028 (USD MILLION)
                       TABLE 108 EUROPE: MARKET, BY TYPE, 2018–2022 (USD MILLION)
                       TABLE 109 EUROPE: MARKET, BY TYPE, 2023–2028 (USD MILLION)
                       TABLE 110 EUROPE: MARKET, BY DATA SOURCE, 2018–2022 (USD MILLION)
                       TABLE 111 EUROPE: MARKET, BY DATA SOURCE, 2023–2028 (USD MILLION)
                       TABLE 112 EUROPE: MARKET, BY MODEL TYPE, 2018–2022 (USD MILLION)
                       TABLE 113 EUROPE: MARKET, BY MODEL TYPE, 2023–2028 (USD MILLION)
                       TABLE 114 EUROPE: MARKET, BY APPLICATION, 2018–2022 (USD MILLION)
                       TABLE 115 EUROPE: MARKET, BY APPLICATION, 2023–2028 (USD MILLION)
                       TABLE 116 EUROPE: MARKET, BY VERTICAL, 2018–2022 (USD MILLION)
                       TABLE 117 EUROPE: MARKET, BY VERTICAL, 2023–2028 (USD MILLION)
                       TABLE 118 EUROPE: MARKET, BY COUNTRY, 2018–2022 (USD MILLION)
                       TABLE 119 EUROPE: MARKET, BY COUNTRY, 2023–2028 (USD MILLION)
             12.3.3 UK
                       12.3.3.1 Government initiatives supporting integration of knowledge graphs to boost market
                                   TABLE 120 UK: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2018–2022 (USD MILLION)
                                   TABLE 121 UK: MARKET, BY OFFERING, 2023–2028 (USD MILLION)
                                   TABLE 122 UK: MARKET, BY TYPE, 2018–2022 (USD MILLION)
                                   TABLE 123 UK: MARKET, BY TYPE, 2023–2028 (USD MILLION)
                                   TABLE 124 UK: MARKET, BY DATA SOURCE, 2018–2022 (USD MILLION)
                                   TABLE 125 UK: MARKET, BY DATA SOURCE, 2023–2028 (USD MILLION)
                                   TABLE 126 UK: MARKET, BY MODEL TYPE, 2018–2022 (USD MILLION)
                                   TABLE 127 UK: MARKET, BY MODEL TYPE, 2023–2028 (USD MILLION)
                                   TABLE 128 UK: MARKET, BY APPLICATION, 2018–2022 (USD MILLION)
                                   TABLE 129 UK: MARKET, BY APPLICATION, 2023–2028 (USD MILLION)
                                   TABLE 130 UK: MARKET, BY VERTICAL, 2018–2022 (USD MILLION)
                                   TABLE 131 UK: MARKET, BY VERTICAL, 2023–2028 (USD MILLION)
             12.3.4 GERMANY
                       12.3.4.1 Increasing digitalization and technological advancements to propel market
             12.3.5 FRANCE
                       12.3.5.1 Rising demand for data management and integration to drive market
             12.3.6 ITALY
                       12.3.6.1 Proliferation of social networks and supply chain networks to boost market
                                   TABLE 132 ITALY: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2018–2022 (USD MILLION)
                                   TABLE 133 ITALY: MARKET, BY OFFERING, 2023–2028 (USD MILLION)
                                   TABLE 134 ITALY: MARKET, BY TYPE, 2018–2022 (USD MILLION)
                                   TABLE 135 ITALY: MARKET, BY TYPE, 2023–2028 (USD MILLION)
                                   TABLE 136 ITALY: MARKET, BY DATA SOURCE, 2018–2022 (USD MILLION)
                                   TABLE 137 ITALY: MARKET, BY DATA SOURCE, 2023–2028 (USD MILLION)
                                   TABLE 138 ITALY: MARKET, BY MODEL TYPE, 2018–2022 (USD MILLION)
                                   TABLE 139 ITALY: MARKET, BY MODEL TYPE, 2023–2028 (USD MILLION)
                                   TABLE 140 ITALY: MARKET, BY APPLICATION, 2018–2022 (USD MILLION)
                                   TABLE 141 ITALY: MARKET, BY APPLICATION, 2023–2028 (USD MILLION)
                                   TABLE 142 ITALY: MARKET, BY VERTICAL, 2018–2022 (USD MILLION)
                                   TABLE 143 ITALY: MARKET, BY VERTICAL, 2023–2028 (USD MILLION)
             12.3.7 SPAIN
                       12.3.7.1 Implementation of knowledge graphs by logistics companies to optimize supply chain operations to accelerate market
             12.3.8 REST OF EUROPE
     12.4 ASIA PACIFIC 
               FIGURE 36 ASIA PACIFIC: MARKET SNAPSHOT
             12.4.1 ASIA PACIFIC: MARKET DRIVERS
             12.4.2 ASIA PACIFIC: RECESSION IMPACT
                       TABLE 144 ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2018–2022 (USD MILLION)
                       TABLE 145 ASIA PACIFIC: MARKET, BY OFFERING, 2023–2028 (USD MILLION)
                       TABLE 146 ASIA PACIFIC: MARKET, BY TYPE,  2018–2022 (USD MILLION)
                       TABLE 147 ASIA PACIFIC: MARKET, BY TYPE,  2023–2028 (USD MILLION)
                       TABLE 148 ASIA PACIFIC: MARKET, BY DATA SOURCE,  2018–2022 (USD MILLION)
                       TABLE 149 ASIA PACIFIC: MARKET, BY DATA SOURCE,  2023–2028 (USD MILLION)
                       TABLE 150 ASIA PACIFIC: MARKET, BY MODEL TYPE,  2018–2022 (USD MILLION)
                       TABLE 151 ASIA PACIFIC: MARKET, BY MODEL TYPE,  2023–2028 (USD MILLION)
                       TABLE 152 ASIA PACIFIC: MARKET, BY APPLICATION,  2018–2022 (USD MILLION)
                       TABLE 153 ASIA PACIFIC: MARKET, BY APPLICATION,  2023–2028 (USD MILLION)
                       TABLE 154 ASIA PACIFIC: MARKET, BY VERTICAL, 2018–2022 (USD MILLION)
                       TABLE 155 ASIA PACIFIC: MARKET, BY VERTICAL, 2023–2028 (USD MILLION)
                       TABLE 156 ASIA PACIFIC: MARKET, BY COUNTRY, 2018–2022 (USD MILLION)
                       TABLE 157 ASIA PACIFIC: MARKET, BY COUNTRY, 2023–2028 (USD MILLION)
             12.4.3 CHINA
                       12.4.3.1 Increasing R&D investments and government support to boost market
                                   TABLE 158 CHINA: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2018–2022 (USD MILLION)
                                   TABLE 159 CHINA: MARKET, BY OFFERING, 2023–2028 (USD MILLION)
                                   TABLE 160 CHINA: MARKET, BY TYPE, 2018–2022 (USD MILLION)
                                   TABLE 161 CHINA: MARKET, BY TYPE, 2023–2028 (USD MILLION)
                                   TABLE 162 CHINA: MARKET, BY DATA SOURCE, 2018–2022 (USD MILLION)
                                   TABLE 163 CHINA: MARKET, BY DATA SOURCE, 2023–2028 (USD MILLION)
                                   TABLE 164 CHINA: MARKET, BY MODEL TYPE, 2018–2022 (USD MILLION)
                                   TABLE 165 CHINA: MARKET, BY MODEL TYPE, 2023–2028 (USD MILLION)
                                   TABLE 166 CHINA: MARKET, BY APPLICATION, 2018–2022 (USD MILLION)
                                   TABLE 167 CHINA: MARKET, BY APPLICATION, 2023–2028 (USD MILLION)
                                   TABLE 168 CHINA: MARKET, BY VERTICAL, 2018–2022 (USD MILLION)
                                   TABLE 169 CHINA: MARKET, BY VERTICAL, 2023–2028 (USD MILLION)
             12.4.4 JAPAN
                       12.4.4.1 Robust technological sector and persistent focus on innovation to boost market
             12.4.5 INDIA
                       12.4.5.1 Increasing adoption of digital services to drive market
             12.4.6 AUSTRALIA & NEW ZEALAND
                       12.4.6.1 Growing infrastructure developments to boost market
             12.4.7 REST OF ASIA PACIFIC
     12.5 MIDDLE EAST & AFRICA 
             12.5.1 MIDDLE EAST & AFRICA: MARKET DRIVERS
             12.5.2 MIDDLE EAST & AFRICA: RECESSION IMPACT
                       TABLE 170 MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET, BY OFFERING,  2018–2022 (USD MILLION)
                       TABLE 171 MIDDLE EAST & AFRICA: MARKET, BY OFFERING,  2023–2028 (USD MILLION)
                       TABLE 172 MIDDLE EAST & AFRICA: MARKET, BY TYPE,  2018–2022 (USD MILLION)
                       TABLE 173 MIDDLE EAST & AFRICA: MARKET, BY TYPE,  2023–2028 (USD MILLION)
                       TABLE 174 MIDDLE EAST & AFRICA: MARKET, BY DATA SOURCE,  2018–2022 (USD MILLION)
                       TABLE 175 MIDDLE EAST & AFRICA: MARKET, BY DATA SOURCE,  2023–2028 (USD MILLION)
                       TABLE 176 MIDDLE EAST & AFRICA: MARKET, BY MODEL TYPE,  2018–2022 (USD MILLION)
                       TABLE 177 MIDDLE EAST & AFRICA: MARKET, BY MODEL TYPE,  2023–2028 (USD MILLION)
                       TABLE 178 MIDDLE EAST & AFRICA: MARKET, BY APPLICATION,  2018–2022 (USD MILLION)
                       TABLE 179 MIDDLE EAST & AFRICA: MARKET, BY APPLICATION,  2023–2028 (USD MILLION)
                       TABLE 180 MIDDLE EAST & AFRICA: MARKET, BY VERTICAL,  2018–2022 (USD MILLION)
                       TABLE 181 MIDDLE EAST & AFRICA: MARKET, BY VERTICAL,  2023–2028 (USD MILLION)
                       TABLE 182 MIDDLE EAST & AFRICA: MARKET, BY COUNTRY,  2018–2022 (USD MILLION)
                       TABLE 183 MIDDLE EAST & AFRICA: MARKET, BY COUNTRY,  2023–2028 (USD MILLION)
             12.5.3 GCC
                       12.5.3.1 Growing awareness of benefits of knowledge graphs to drive market
             12.5.4 SOUTH AFRICA
                       12.5.4.1 Pivotal role of knowledge graphs in driving innovation and informed decision-making to fuel market growth
             12.5.5 REST OF MIDDLE EAST & AFRICA
     12.6 LATIN AMERICA 
             12.6.1 LATIN AMERICA: MARKET DRIVERS
             12.6.2 LATIN AMERICA: RECESSION IMPACT
                       TABLE 184 LATIN AMERICA: KNOWLEDGE GRAPH MARKET, BY OFFERING,  2018–2022 (USD MILLION)
                       TABLE 185 LATIN AMERICA: MARKET, BY OFFERING,  2023–2028 (USD MILLION)
                       TABLE 186 LATIN AMERICA: MARKET, BY TYPE,  2018–2022 (USD MILLION)
                       TABLE 187 LATIN AMERICA: MARKET, BY TYPE,  2023–2028 (USD MILLION)
                       TABLE 188 LATIN AMERICA: MARKET, BY DATA SOURCE,  2018–2022 (USD MILLION)
                       TABLE 189 LATIN AMERICA: MARKET, BY DATA SOURCE,  2023–2028 (USD MILLION)
                       TABLE 190 LATIN AMERICA: MARKET, BY MODEL TYPE,  2018–2022 (USD MILLION)
                       TABLE 191 LATIN AMERICA: MARKET, BY MODEL TYPE,  2023–2028 (USD MILLION)
                       TABLE 192 LATIN AMERICA: MARKET, BY APPLICATION,  2018–2022 (USD MILLION)
                       TABLE 193 LATIN AMERICA: MARKET, BY APPLICATION,  2023–2028 (USD MILLION)
                       TABLE 194 LATIN AMERICA: MARKET, BY VERTICAL, 2018–2022 (USD MILLION)
                       TABLE 195 LATIN AMERICA: MARKET, BY VERTICAL, 2023–2028 (USD MILLION)
                       TABLE 196 LATIN AMERICA: MARKET, BY COUNTRY,  2018–2022 (USD MILLION)
                       TABLE 197 LATIN AMERICA: MARKET, BY COUNTRY,  2023–2028 (USD MILLION)
             12.6.3 BRAZIL
                       12.6.3.1 Spike in demand for quick and real-time data access to propel market
             12.6.4 MEXICO
                       12.6.4.1 Rising need for efficient data management and growing adoption of AI & ML technologies to drive market
             12.6.5 REST OF LATIN AMERICA
 
13 COMPETITIVE LANDSCAPE (Page No. - 178)
     13.1 OVERVIEW 
     13.2 STRATEGIES ADOPTED BY KEY PLAYERS 
               TABLE 198 OVERVIEW OF STRATEGIES ADOPTED BY KEY PLAYERS IN MARKET
     13.3 COMPETITIVE SCENARIO 
     13.4 MARKET SHARE ANALYSIS 
               TABLE 199 MARKET: DEGREE OF COMPETITION
     13.5 HISTORICAL REVENUE ANALYSIS 
               FIGURE 37 HISTORICAL THREE-YEAR REVENUE ANALYSIS OF LEADING PLAYERS,  2020–2022 (USD MILLION)
     13.6 RANKING OF KEY PLAYERS IN KNOWLEDGE GRAPH  MARKET, 2023 
               FIGURE 38 MARKET RANKING OF KEY PLAYERS, 2023
     13.7 COMPANY EVALUATION MATRIX METHODOLOGY 
               FIGURE 39 COMPANY EVALUATION MATRIX: CRITERIA WEIGHTAGE
             13.7.1 STARS
             13.7.2 EMERGING LEADERS
             13.7.3 PERVASIVE PLAYERS
             13.7.4 PARTICIPANTS
                       FIGURE 40 KNOWLEDGE GRAPH MARKET: COMPANY EVALUATION MATRIX, 2023
     13.8 STARTUP/SME EVALUATION MATRIX METHODOLOGY  AND DEFINITIONS 
               FIGURE 41 STARTUP/SME EVALUATION MATRIX: CRITERIA WEIGHTAGE
             13.8.1 PROGRESSIVE COMPANIES
             13.8.2 RESPONSIVE COMPANIES
             13.8.3 DYNAMIC COMPANIES
             13.8.4 STARTING BLOCKS
                       FIGURE 42 MARKET: STARTUP/SME EVALUATION MATRIX
     13.9 COMPANY FOOTPRINT 
               TABLE 200 MARKET: COMPANY FOOTPRINT ANALYSIS
     13.10 COMPETITIVE BENCHMARKING 
               TABLE 201 DETAILED LIST OF STARTUPS/SMES
               TABLE 202 COMPETITIVE BENCHMARKING OF STARTUPS/SMES
               TABLE 203 COMPETITIVE BENCHMARKING OF KEY PLAYERS
     13.11 COMPETITIVE SCENARIO 
               13.11.1 PRODUCT LAUNCHES
                       TABLE 204 MARKET: PRODUCT LAUNCHES, 2019–2023
               13.11.2 DEALS
                       TABLE 205 KNOWLEDGE GRAPH MARKET: DEALS, 2019–2023
     13.12 KNOWLEDGE GRAPH PRODUCT BENCHMARKING 
                       TABLE 206 COMPARATIVE ANALYSIS OF PROMINENT KNOWLEDGE GRAPH SOLUTIONS
     13.13 VALUATION AND FINANCIAL METRICS OF KEY KNOWLEDGE GRAPH VENDORS 
                       FIGURE 43 VALUATION AND FINANCIAL METRICS OF KNOWLEDGE GRAPH VENDORS
 
14 COMPANY PROFILES (Page No. - 193)
(Business overview, Products/Solutions/Services offered, Recent Developments, MNM view)*
     14.1 KEY PLAYERS 
             14.1.1 IBM
                       TABLE 207 IBM: BUSINESS OVERVIEW
                       FIGURE 44 IBM: COMPANY SNAPSHOT
                       TABLE 208 IBM: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                       TABLE 209 IBM: PRODUCT LAUNCHES/ENHANCEMENTS
                       TABLE 210 IBM: DEALS
             14.1.2 MICROSOFT
                       TABLE 211 MICROSOFT: BUSINESS OVERVIEW
                       FIGURE 45 MICROSOFT: COMPANY SNAPSHOT
                       TABLE 212 MICROSOFT: PRODUCTS/SOLUTIONS/SERVICES OFFERED
             14.1.3 AWS
                       TABLE 213 AWS: COMPANY OVERVIEW
                       FIGURE 46 AWS: COMPANY SNAPSHOT
                       TABLE 214 AWS: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                       TABLE 215 AWS: PRODUCT LAUNCHES/ENHANCEMENTS
                       TABLE 216 AWS: DEALS
             14.1.4 NEO4J
                       TABLE 217 NEO4J: COMPANY OVERVIEW
                       TABLE 218 NEO4J: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                       TABLE 219 NEO4J: PRODUCT LAUNCHES/ENHANCEMENTS
                       TABLE 220 NEO4J: DEALS
             14.1.5 TIGERGRAPH
                       TABLE 221 TIGERGRAPH: COMPANY OVERVIEW
                       TABLE 222 TIGERGRAPH: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                       TABLE 223 TIGERGRAPH: DEALS
             14.1.6 SAP
                       TABLE 224 SAP: BUSINESS OVERVIEW
                       FIGURE 47 SAP: COMPANY SNAPSHOT
                       TABLE 225 SAP: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                       TABLE 226 SAP: DEALS
             14.1.7 ORACLE
                       TABLE 227 ORACLE: COMPANY OVERVIEW
                       FIGURE 48 ORACLE: COMPANY SNAPSHOT
                       TABLE 228 ORACLE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                       TABLE 229 ORACLE: PRODUCT LAUNCHES/ENHANCEMENTS
             14.1.8 STARDOG
                       TABLE 230 STARDOG: COMPANY OVERVIEW
                       TABLE 231 STARDOG: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                       TABLE 232 STARDOG: PRODUCT LAUNCHES/ENHANCEMENTS
                       TABLE 233 STARDOG: DEALS
             14.1.9 FRANZ INC.
                       TABLE 234 FRANZ INC.: COMPANY OVERVIEW
                       TABLE 235 FRANZ INC.: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                       TABLE 236 FRANZ INC.: PRODUCT LAUNCHES/ENHANCEMENTS
                       TABLE 237 FRANZ INC.: DEALS
             14.1.10 ONTOTEXT
                       TABLE 238 ONTOTEXT: COMPANY OVERVIEW
                       TABLE 239 ONTOTEXT: PRODUCTS/SOLUTIONS/SERVICES OFFERED
                       TABLE 240 ONTOTEXT: PRODUCT LAUNCHES/ENHANCEMENTS
                       TABLE 241 ONTOTEXT: DEALS
             14.1.11 SEMANTIC WEB COMPANY
             14.1.12 OPENLINK SOFTWARE
             14.1.13 MARKLOGIC
     14.2 OTHER PLAYERS/STARTUPS 
             14.2.1 DATAVID
             14.2.2 GRAPHBASE
             14.2.3 CAMBRIDGE SEMANTICS
             14.2.4 CONVERSIGHT
             14.2.5 ECCENA
             14.2.6 ARANGODB
             14.2.7 FLUREE
             14.2.8 DIFFBOT
             14.2.9 BITNINE
             14.2.10 MEMGRAPH
             14.2.11 GRAPHAWARE
             14.2.12 ONLIM
*Details on Business overview, Products/Solutions/Services offered, Recent Developments, MNM view might not be captured in case of unlisted companies.
 
15 ADJACENT/RELATED MARKETS (Page No. - 228)
     15.1 INTRODUCTION TO ADJACENT MARKETS 
               TABLE 242 ADJACENT MARKETS AND FORECASTS
     15.2 LIMITATIONS 
     15.3 GRAPH DATABASE MARKET 
               TABLE 243 GRAPH DATABASE MARKET, BY OFFERING, 2018–2022 (USD MILLION)
               TABLE 244 GRAPH DATABASE MARKET, BY OFFERING, 2023–2028 (USD MILLION)
               TABLE 245 GRAPH DATABASE MARKET, BY MODEL TYPE, 2018–2022 (USD MILLION)
               TABLE 246 GRAPH DATABASE MARKET, BY MODEL TYPE, 2023–2028 (USD MILLION)
               TABLE 247 GRAPH DATABASE MARKET, BY ANALYSIS TYPE, 2018–2022 (USD MILLION)
               TABLE 248 GRAPH DATABASE MARKET, BY ANALYSIS TYPE, 2023–2028 (USD MILLION)
               TABLE 249 GRAPH DATABASE MARKET, BY VERTICAL, 2018–2022 (USD MILLION)
               TABLE 250 GRAPH DATABASE MARKET, BY VERTICAL, 2023–2028 (USD MILLION)
               TABLE 251 GRAPH DATABASE MARKET, BY REGION, 2018–2022 (USD MILLION)
               TABLE 252 GRAPH DATABASE MARKET, BY REGION, 2023–2028 (USD MILLION)
     15.4 NATURAL LANGUAGE PROCESSING (NLP) MARKET 
               TABLE 253 NATURAL LANGUAGE PROCESSING MARKET, BY OFFERING, 2017–2022 (USD MILLION)
               TABLE 254 NATURAL LANGUAGE PROCESSING MARKET, BY OFFERING, 2023–2028 (USD MILLION)
               TABLE 255 NATURAL LANGUAGE PROCESSING MARKET, BY TYPE, 2017–2022 (USD MILLION)
               TABLE 256 NATURAL LANGUAGE PROCESSING MARKET, BY TYPE, 2023–2028 (USD MILLION)
               TABLE 257 FRAUD DETECTION AND PREVENTION MARKET, BY OFFERING,  2023–2028 (USD MILLION)
               TABLE 258 NATURAL LANGUAGE PROCESSING MARKET, BY APPLICATION,  2017–2022 (USD MILLION)
               TABLE 259 NATURAL LANGUAGE PROCESSING MARKET, BY APPLICATION,  2023–2028 (USD MILLION)
               TABLE 260 NATURAL LANGUAGE PROCESSING MARKET, BY TECHNOLOGY,  2017–2022 (USD MILLION)
               TABLE 261 NATURAL LANGUAGE PROCESSING MARKET, BY TECHNOLOGY,  2023–2028 (USD MILLION)
               TABLE 262 NATURAL LANGUAGE PROCESSING MARKET, BY VERTICAL, 2017–2022 (USD MILLION)
               TABLE 263 NATURAL LANGUAGE PROCESSING MARKET, BY VERTICAL, 2023–2028 (USD MILLION)
               TABLE 264 NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION)
               TABLE 265 NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION)
 
16 APPENDIX (Page No. - 236)
     16.1 DISCUSSION GUIDE 
     16.2 KNOWLEDGESTORE: MARKETSANDMARKETS’  SUBSCRIPTION PORTAL 
     16.3 CUSTOMIZATION OPTIONS 
     16.4 RELATED REPORTS 
     16.5 AUTHOR DETAILS 

The study involved four major activities in estimating the current size of the global knowledge graph market. Exhaustive secondary research was done to collect information on the market, peer market, and parent market. The next step was to validate these findings, assumptions, and sizing with industry experts across the value chain through primary research. Both top-down and bottom-up approaches were employed to estimate the total knowledge graph market size. After that, the market breakup and data triangulation techniques were used to estimate the market size of segments and subsegments.

Secondary Research

In the secondary research process, various secondary sources, such as Bloomberg and BusinessWeek, have been referred to identify and collect information for this study. The secondary sources included annual reports, press releases, and investor presentations of companies; white papers; and journals, such as Linux Journal and Container Journal, and articles from recognized authors, directories, and databases.

Primary Research

Various primary sources from both supply and demand sides were interviewed to obtain qualitative and quantitative information for this report. The primary sources from the supply side included industry experts, such as Chief Executive Officers (CEOs), Chief Marketing Officers (CMO), Vice Presidents (VPs), Managing Directors (MDs), technology and innovation directors, and related key executives from various key companies and organizations operating in the knowledge graph market along with the associated service providers, and system integrators operating in the targeted regions. All possible parameters that affect the market covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data. Following is the breakup of primary respondents.

Knowledge Graph Market Size, and Share

Company Name

Designation

Neo4j

Senior Manager

Stardog

VP

IBM

Business Executive

Market Size Estimation

For making market estimates and forecasting the knowledge graph market, and other dependent submarkets, the top-down and bottom-up approaches were used. The bottom-up procedure was used to arrive at the overall market size of the global knowledge graph market using key companies’ revenue and their offerings in the market. The research methodology used to estimate the market size includes the following:

  • The key players in the knowledge graph market have been identified through extensive secondary research.
  • The market size, in terms of value, has been determined through primary and secondary research processes.
  • All percentage shares, splits, and breakups have been determined using secondary sources and verified through primary sources.

Knowledge graph market Size: Bottom-Up Approach

Knowledge Graph Market Size, and Share

To know about the assumptions considered for the study, Request for Free Sample Report

Knowledge graph market Size: Top-Down Approach

Knowledge Graph Market Size, and Share

Data Triangulation

With data triangulation and validation through primary interviews, the exact value of the overall parent market size was determined and confirmed using this study. The overall market size was then used in the top-down procedure to estimate the size of other individual markets via percentage splits of the market segmentation.

Unlike traditional databases, which typically store data in a flat structure, knowledge graphs use a graph database model to represent data as nodes and edges. Nodes represent entities, such as people, places, and things. Edges represent relationships between entities.

Market Definition

Knowledge graphs are networks of interconnected data that describe real-world entities and their relationships. They are more than just static databases of facts; they can be used to generate new knowledge and insights.

Key Stakeholders

  • Knowledge Graph Solution Providers
  • Independent Software Vendors (ISVs)
  • Investors and Venture Capitalists (VCs)
  • Managed Service Providers
  • Support and Maintenance Service Providers
  • System Integrators (SIs)/Migration Service Providers
  • Value-Added Resellers (VARs) and Distributors

Report Objectives

  • To determine, segment, and forecast the global knowledge graph market by offering, model type, application, type, vertical, and region in terms of value.
  • To forecast the size of the market segments to five main regions: North America, Europe, Asia Pacific, Middle East & Africa, and Latin America 
  • To provide detailed information about the major factors (drivers, opportunities, threats, and challenges) influencing the growth of the market
  • To study the complete value chain and related industry segments and perform a value chain analysis of the market landscape.
  • To strategically analyze the macro and micro markets to individual growth trends, prospects, and contributions to the total market
  • To analyze the industry trends, pricing data, patents, and innovations related to the market.
  • To analyze the opportunities for stakeholders by identifying the high-growth segments of the knowledge graph market
  • To profile the key players in the market and comprehensively analyze their market share/ranking and core competencies.
  • To track and analyze competitive developments, such as mergers & acquisitions, product launches & developments, partnerships, agreements, collaborations, business expansions, and Research & Development (R&D) activities.

Available Customizations

With the given market data, MarketsandMarkets offers customizations as per the company’s specific needs. The following customization options are available for the report:

Company Information

  • Detailed analysis and profiling of an additional two market players
Custom Market Research Services

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Published ON
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