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全球知識圖譜市場：按產品、模型類型、應用、產業、地區分類 - 到 2030 年的預測
市場調查報告書
商品編碼
1633537

全球知識圖譜市場：按產品、模型類型、應用、產業、地區分類 - 到 2030 年的預測

Knowledge Graph Market by Solution (Enterprise Knowledge Graph Platform, Graph Database Engine, Knowledge Management Toolset), Model Type (Resource Description Framework (RDF) Triple Stores, Labeled Property Graph) - Global Forecast to 2030
出版日期: | 出版商: MarketsandMarkets | 英文 360 Pages | 訂單完成後即時交付

價格

知識圖譜市場規模預計到 2024 年將達到 10.684 億美元，到 2030 年將達到 69.384 億美元，年複合成長率（CAGR）為 36.6%。

透過人工智慧建立智慧知識圖預計將改變組織處理大型資料的方式。在識別和提取不同資料點之間的關係時，人為干預顯著減少。自動化包括大多數類型的自然語言處理 (NLP)、機器學習演算法等，用於自動解釋非結構化或結構化資料、識別相關模式並將此類相關資訊關聯起來，包括由人工智慧驅動的工具執行的過程。這種自動化可以加快圖形建構速度，同時提高準確性，確保圖形中表示的關係對於最終使用者而言盡可能相關且最新。

調查範圍
調查年份 2019-2030
基準年 2024年
預測期 2024-2030
考慮單位 金額（百萬美元）
按細分市場 按產品、按型號、按應用、按行業、按地區
目標區域 北美、歐洲、亞太地區、中東非洲、拉丁美洲

圖資料庫引擎是一種特殊類型的資料庫，專門用於高效儲存、管理和搜尋由圖關係（邊）相關的圖資料實體（節點）。由於圖資料庫將資料組織為關係而不是傳統關係系統中的表格，因此它們非常適合資料關係最重要的應用程式，例如社交網路、建議引擎和詐欺檢測 - 在場景中很有用。它還可以快速查詢和遍歷複雜、連結重的資料集，從而產生更自然、直覺、靈活的資料查詢機制。此外，它還支援SPARQL和Cypher等圖特定查詢語言，這些語言針對關係查詢進行了最佳化，提高了圖應用程式的效能和可擴展性。

知識圖服務包括用於實施、增強和維護知識圖解決方案的專業和託管服務。專業服務包括策略設計和開發諮詢、資料整合以及創建與您的業務相關的自訂知識圖。另一方面，託管服務為知識圖平台的效能、可擴充性和安全性提供支援、維護和監控。這些服務以自己的方式幫助客戶取得知識圖譜，從而獲得更好的資料、決策智慧和人工智慧。

亞太地區的特點是旨在支持全部區域圖形技術的採用和應用的舉措和創新。 2021 年，Neo4j推出了Graphs4APAC舉措，為亞太地區的專業人士提供免費培訓、材料和工具，以發展和提高他們的圖形技術知識和技能。這項開放原始碼舉措已在印尼和新加坡成功實施。富士通也參與了生成式人工智慧加速器挑戰賽 (GENIAC) 計劃，該計劃專注於創建專用的大規模語言模型 (LLM)，以產生知識圖並在此類圖上進行推理。由人工智慧驅動的圖表。這些是該地區開始專注於將知識圖應用於創新平台和資料驅動解決方案的關鍵指標。

該報告研究了全球知識圖譜市場，包括按產品、模型類型、應用、行業、地區和參與市場的公司概況分類的趨勢。

目錄

第1章簡介

第2章調查方法

第3章執行摘要

第 4 章重要考察

第5章市場概況及產業趨勢

  • 介紹
  • 市場動態
  • 影響客戶業務的趨勢/干擾
  • 價格分析
  • 供應鏈分析
  • 生態系統
  • 技術分析
  • 專利分析
  • 2024-2025年重大會議和活動
  • 監管狀況
  • 波特五力分析
  • 主要相關人員和採購標準
  • 知識圖譜簡史
  • 建構知識圖譜的步驟
  • 人工智慧/生成式人工智慧對知識圖譜市場的影響
  • 投資金籌措場景
  • 案例研究分析

第 6 章知識圖市場，依產品分類

  • 介紹
  • 解決方案
  • 服務

第 7 章知識圖市場，依模型類型

  • 介紹
  • 資源說明框架 (RDF) 三重存儲
  • 標記屬性圖 (LPG)

第 8 章知識圖譜市場（按應用）

  • 介紹
  • 資料管治與主資料管理
  • 資料分析和商業智慧
  • 知識和內容管理
  • 虛擬助理、自助資料和數位資產發現
  • 產品和配置管理
  • 基礎設施和資產管理
  • 流程最佳化與資源管理
  • 風險管理、合規和監管報告
  • 市場和客戶資訊、銷售最佳化
  • 其他

第 9 章知識圖譜市場（按產業）

  • 介紹
  • BFSI
  • 零售/電子商務
  • 醫療保健、生命科學、製藥
  • 通訊/科技
  • 政府
  • 製造/汽車
  • 媒體娛樂
  • 能源、公共和基礎設施
  • 旅遊/酒店業
  • 運輸和物流
  • 其他

第10章知識圖市場，依地區

  • 介紹
  • 北美洲
    • 北美：宏觀經濟前景
    • 美國
    • 加拿大
  • 歐洲
    • 歐洲：宏觀經濟前景
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 北歐國家
    • 其他
  • 亞太地區
    • 亞太地區：宏觀經濟展望
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲和紐西蘭
    • 其他
  • 中東/非洲
    • 中東和非洲：宏觀經濟前景
    • 海灣合作理事會國家
    • 南非
    • 其他
  • 拉丁美洲
    • 拉丁美洲：宏觀經濟前景
    • 巴西
    • 墨西哥
    • 阿根廷
    • 其他

第11章競爭格局

  • 介紹
  • 主要參與企業的策略/優勢
  • 收益分析
  • 市場佔有率分析
  • 市場排名分析
  • 企業評估矩陣：主要參與企業，2023
  • 企業評估矩陣：Start-Ups/小型企業，2024 年
  • 競爭格局及趨勢
  • 品牌/產品比較
  • 領先知識圖譜解決方案供應商的公司估值和財務指標

第12章 公司簡介

  • 主要參與企業
    • NEO4J
    • AMAZON WEB SERVICES, INC
    • TIGERGRAPH
    • GRAPHWISE
    • RELATIONALAI
    • IBM
    • MICROSOFT
    • SAP
    • ORACLE
    • STARDOG
    • ONTOTEXT
    • FRANZ INC.
    • ALTAIR
    • PROGRESS SOFTWARE CORPORATION
    • ESRI
    • SEMANTIC WEB COMPANY
    • OPENLINK SOFTWARE
  • 小型企業/Start-Ups
    • DATAVID
    • GRAPHBASE
    • CONVERSIGHT
    • ECCENCA
    • ARANGODB
    • FLUREE
    • DIFFBOT
    • BITNINE
    • MEMGRAPH
    • GRAPHAWARE
    • ONLIM
    • SMABBLER
    • WISECUBE
    • METAPHACTS

第13章鄰近/相關市場

第14章附錄

Product Code: TC 8832

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%. 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.

Scope of the Report
Years Considered for the Study2019-2030
Base Year2024
Forecast Period2024-2030
Units ConsideredValue (USD Million)
SegmentsBy Solutions, Services, Model Type, Vertical.
Regions coveredNorth America, Europe, Asia Pacific, Middle East & Africa, Latin America

"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

  • 1.1 STUDY OBJECTIVES
  • 1.2 MARKET DEFINITION
    • 1.2.1 INCLUSIONS AND EXCLUSIONS
  • 1.3 STUDY SCOPE
    • 1.3.1 MARKET SEGMENTATION
    • 1.3.2 YEARS CONSIDERED
  • 1.4 CURRENCY CONSIDERED
  • 1.5 STAKEHOLDERS
  • 1.6 SUMMARY OF CHANGES

2 RESEARCH METHODOLOGY

  • 2.1 RESEARCH DATA
    • 2.1.1 SECONDARY DATA
      • 2.1.1.1 Key data from secondary sources
    • 2.1.2 PRIMARY DATA
      • 2.1.2.1 Primary interviews with experts
      • 2.1.2.2 Breakdown of primary interviews
      • 2.1.2.3 Key insights from industry experts
  • 2.2 MARKET SIZE ESTIMATION
    • 2.2.1 TOP-DOWN APPROACH
      • 2.2.1.1 Supply-side analysis
    • 2.2.2 BOTTOM-UP APPROACH
      • 2.2.2.1 Demand-side analysis
  • 2.3 DATA TRIANGULATION
  • 2.4 RESEARCH ASSUMPTIONS
  • 2.5 RESEARCH LIMITATIONS
  • 2.6 RISK ASSESSMENT

3 EXECUTIVE SUMMARY

4 PREMIUM INSIGHTS

  • 4.1 ATTRACTIVE OPPORTUNITIES FOR KEY PLAYERS IN KNOWLEDGE GRAPH MARKET
  • 4.2 KNOWLEDGE GRAPH MARKET, BY OFFERING
  • 4.3 KNOWLEDGE GRAPH MARKET, BY SERVICE
  • 4.4 KNOWLEDGE GRAPH MARKET, BY MODEL TYPE
  • 4.5 KNOWLEDGE GRAPH MARKET, BY APPLICATION 60
  • 4.6 KNOWLEDGE GRAPH MARKET, BY VERTICAL
  • 4.7 NORTH AMERICA: KNOWLEDGE GRAPH MARKET, SOLUTIONS AND SERVICES

5 MARKET OVERVIEW AND INDUSTRY TRENDS

  • 5.1 INTRODUCTION
  • 5.2 MARKET DYNAMICS
    • 5.2.1 DRIVERS
      • 5.2.1.1 Rising demand for AI/generative AI solutions
      • 5.2.1.2 Rapid growth in data volume and complexity
      • 5.2.1.3 Growing demand for semantic search
    • 5.2.2 RESTRAINTS
      • 5.2.2.1 Data quality and integration challenges
      • 5.2.2.2 Navigation of saturated data management tool landscape
      • 5.2.2.3 Scalability issues
    • 5.2.3 OPPORTUNITIES
      • 5.2.3.1 Leveraging LLMs to reduce knowledge graph construction costs
      • 5.2.3.2 Data unification and rapid proliferation of knowledge graphs
      • 5.2.3.3 Increasing adoption in healthcare and life sciences to revolutionize data management and enhance patient outcomes
    • 5.2.4 CHALLENGES
      • 5.2.4.1 Lack of expertise and awareness
      • 5.2.4.2 Standardization and interoperability
      • 5.2.4.3 Difficulty in demonstrating full value of knowledge graphs through single use cases
  • 5.3 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
  • 5.4 PRICING ANALYSIS
    • 5.4.1 PRICE TREND OF KEY PLAYERS, BY SOLUTION
    • 5.4.2 INDICATIVE PRICING ANALYSIS OF KEY PLAYERS
  • 5.5 SUPPLY CHAIN ANALYSIS
  • 5.6 ECOSYSTEM
  • 5.7 TECHNOLOGY ANALYSIS
    • 5.7.1 KEY TECHNOLOGIES
      • 5.7.1.1 Graph Databases (GDB)
      • 5.7.1.2 Semantic web technologies
      • 5.7.1.3 Generative AI and Natural Language Processing (NLP)
      • 5.7.1.4 GraphRAG
    • 5.7.2 COMPLEMENTARY TECHNOLOGIES
      • 5.7.2.1 Artificial Intelligence (AI) and Machine Learning (ML)
      • 5.7.2.2 Big data
      • 5.7.2.3 Graph Neural Networks (GNNS)
      • 5.7.2.4 Cloud computing
      • 5.7.2.5 Vector databases and Full-Text Search Engines (FTS)
      • 5.7.2.6 Multi-model databases
    • 5.7.3 ADJACENT TECHNOLOGIES
      • 5.7.3.1 Digital twin
      • 5.7.3.2 Internet of Things (IoT)
      • 5.7.3.3 Blockchain
      • 5.7.3.4 Edge computing
  • 5.8 PATENT ANALYSIS
    • 5.8.1 METHODOLOGY
      • 5.8.1.1 List of major patents
  • 5.9 KEY CONFERENCES AND EVENTS, 2024-2025
  • 5.10 REGULATORY LANDSCAPE
    • 5.10.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
    • 5.10.2 KEY REGULATIONS
      • 5.10.2.1 North America
        • 5.10.2.1.1 SCR 17: Artificial Intelligence Bill (California)
        • 5.10.2.1.2 S1103: Artificial Intelligence Automated Decision Bill (Connecticut)
        • 5.10.2.1.3 National Artificial Intelligence Initiative Act (NAIIA)
        • 5.10.2.1.4 The Artificial Intelligence and Data Act (AIDA) - Canada
      • 5.10.2.2 Europe
        • 5.10.2.2.1 The European Union (EU) - Artificial Intelligence Act (AIA)
        • 5.10.2.2.2 EU Data Governance Act
        • 5.10.2.2.3 General Data Protection Regulation (Europe)
      • 5.10.2.3 Asia Pacific
        • 5.10.2.3.1 Interim Administrative Measures for Generative Artificial Intelligence Services (China)
        • 5.10.2.3.2 The National AI Strategy (Singapore)
        • 5.10.2.3.3 The Hiroshima AI Process Comprehensive Policy Framework (Japan)
      • 5.10.2.4 Middle East & Africa
        • 5.10.2.4.1 The National Strategy for Artificial Intelligence (UAE)
        • 5.10.2.4.2 The National Artificial Intelligence Strategy (Qatar)
        • 5.10.2.4.3 The AI Ethics Principles and Guidelines (Dubai)
      • 5.10.2.5 Latin America
        • 5.10.2.5.1 The Santiago Declaration (Chile)
        • 5.10.2.5.2 The Brazilian Artificial Intelligence Strategy (EBIA)
  • 5.11 PORTER'S FIVE FORCES ANALYSIS
    • 5.11.1 THREAT OF NEW ENTRANTS
    • 5.11.2 THREAT OF SUBSTITUTES
    • 5.11.3 BARGAINING POWER OF BUYERS
    • 5.11.4 BARGAINING POWER OF SUPPLIERS
    • 5.11.5 INTENSITY OF COMPETITIVE RIVALRY 92
  • 5.12 KEY STAKEHOLDERS & BUYING CRITERIA
    • 5.12.1 KEY STAKEHOLDERS IN BUYING PROCESS
    • 5.12.2 BUYING CRITERIA
  • 5.13 BRIEF HISTORY OF KNOWLEDGE GRAPH
  • 5.14 STEPS TO BUILD KNOWLEDGE GRAPH
    • 5.14.1 DEFINE OBJECTIVES
    • 5.14.2 ENGAGE STAKEHOLDERS
    • 5.14.3 IDENTIFY KNOWLEDGE DOMAIN
    • 5.14.4 GATHER AND ANALYZE DATA
    • 5.14.5 CLEAN AND PREPROCESS DATA
    • 5.14.6 CREATE SEMANTIC DATA MODEL
    • 5.14.7 SCHEMA DEFINITION
    • 5.14.8 DATA INTEGRATION
    • 5.14.9 HARMONIZATION OF DATA
    • 5.14.10 BUILD KNOWLEDGE GRAPH
    • 5.14.11 AUGMENT GRAPH
    • 5.14.12 TESTING AND VALIDATION
    • 5.14.13 MAXIMIZE USABILITY
    • 5.14.14 CONTINUOUS MAINTENANCE AND EVOLUTION
  • 5.15 IMPACT OF AI/GENERATIVE AI ON KNOWLEDGE GRAPH MARKET
    • 5.15.1 USE CASES OF GENERATIVE KNOWLEDGE GRAPH
  • 5.16 INVESTMENT AND FUNDING SCENARIO
  • 5.17 CASE STUDY ANALYSIS
    • 5.17.1 TRANSMISSION SYSTEM OPERATOR LEVERAGED ONTOTEXT'S SOLUTIONS TO MODERNIZE ASSET MANAGEMENT
    • 5.17.2 BOSTON SCIENTIFIC STREAMLINED MEDICAL SUPPLY CHAIN USING NEO4J'S GRAPH DATA SCIENCE SOLUTION
    • 5.17.3 NATIONAL RETAIL CHAIN FROM UK ENHANCED OPERATIONAL EFFICIENCY USING TIGERGRAPHS'S SOLUTION
    • 5.17.4 SCHNEIDER ELECTRIC USED STARDOG TO LEAD SMART BUILDING TRANSFORMATION
    • 5.17.5 MEDIA ORGANIZATION USED PROGRESS SEMAPHORE TO CLASSIFY CONTENT FOR BETTER AUDIENCE ENGAGEMENT
    • 5.17.6 YAHOO7 REPRESENTED CONTENT WITHIN KNOWLEDGE GRAPH WITH ASSISTANCE OF BLAZEGRAPH
    • 5.17.7 DATABASE GROUP HELPED SPRINGERMATERIALS ACCELERATE RESEARCH WITH SEMANTIC SEARCH
    • 5.17.8 RFS OPTIMIZED ITS GLOBAL PRODUCT AND INVENTORY MANAGEMENT BY USING ECCENCA'S SOLUTION 104

6 KNOWLEDGE GRAPH MARKET, BY OFFERING

  • 6.1 INTRODUCTION
    • 6.1.1 OFFERINGS: KNOWLEDGE GRAPH MARKET DRIVERS
  • 6.2 SOLUTIONS
    • 6.2.1 SPIKE IN DEMAND FOR SOPHISTICATED DATA MANAGEMENT AND ANALYSIS TO DRIVE MARKET
    • 6.2.2 ENTERPRISE KNOWLEDGE GRAPH PLATFORM
      • 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
    • 6.2.3 GRAPH DATABASE ENGINE
      • 6.2.3.1 Features like parallel query execution and AI-driven insights in graph database engines to accelerate market growth
    • 6.2.4 KNOWLEDGE MANAGEMENT TOOLSET
      • 6.2.4.1 Knowledge management toolsets to enhance operational efficiency by enabling seamless access to organizational knowledge
  • 6.3 SERVICES
    • 6.3.1 PROFESSIONAL SERVICES
    • 6.3.2 MANAGED SERVICES

7 KNOWLEDGE GRAPH MARKET, BY MODEL TYPE

  • 7.1 INTRODUCTION
    • 7.1.1 MODEL TYPES: KNOWLEDGE GRAPH MARKET DRIVERS
  • 7.2 RESOURCE DESCRIPTION FRAMEWORK (RDF) TRIPLE STORES
    • 7.2.1 RDF-BASED KNOWLEDGE GRAPHS TO FACILITATE APPLICATIONS REQUIRING SEMANTIC INTEROPERABILITY
  • 7.3 LABELED PROPERTY GRAPH (LPG)
    • 7.3.1 LOGICAL INFERENCE, KNOWLEDGE DISCOVERY, AND STRUCTURED REPRESENTATION OF DATA TO BOOST MARKET GROWTH

8 KNOWLEDGE GRAPH MARKET, BY APPLICATION

  • 8.1 INTRODUCTION
    • 8.1.1 APPLICATIONS: KNOWLEDGE GRAPH MARKET DRIVERS
  • 8.2 DATA GOVERNANCE AND MASTER DATA MANAGEMENT
    • 8.2.1 NEED FOR ENHANCED SEARCH FUNCTIONALITIES TO BOLSTER MARKET GROWTH
  • 8.3 DATA ANALYTICS & BUSINESS INTELLIGENCE
    • 8.3.1 INTEGRATION OF KNOWLEDGE FROM SEVERAL DISCIPLINES AND OFFERING PERSONALIZED RECOMMENDATIONS TO BOOST MARKET GROWTH
  • 8.4 KNOWLEDGE & CONTENT MANAGEMENT
    • 8.4.1 WIDESPREAD KNOWLEDGE OF INTRICATE IDEAS THROUGH CROSS-DOMAIN INFORMATION INTEGRATION TO BOOST MARKET
  • 8.5 VIRTUAL ASSISTANTS, SELF-SERVICE DATA, AND DIGITAL ASSET DISCOVERY
    • 8.5.1 STREAMLINING OF TEAMWORK AND KNOWLEDGE EXCHANGE TO ACCELERATE MARKET GROWTH
  • 8.6 PRODUCT & CONFIGURATION MANAGEMENT
    • 8.6.1 NEED TO ENSURE ACCURACY AND REDUCES TIME-TO-MARKET ENHANCING CUSTOMER SATISFACTION TO FUEL MARKET GROWTH
  • 8.7 INFRASTRUCTURE & ASSET MANAGEMENT
    • 8.7.1 INFRASTRUCTURE AND ASSET MANAGEMENT TO REDUCE DOWNTIME AND EXTEND ASSET LIFECYCLES THROUGH INFORMED DECISION-MAKING PROCESSES
  • 8.8 PROCESS OPTIMIZATION & RESOURCE MANAGEMENT
    • 8.8.1 NEED FOR REAL-TIME RESOURCE UTILIZATION MONITORING ACROSS DIFFERENT PROJECTS OR DEPARTMENTS TO PROPEL MARKET
  • 8.9 RISK MANAGEMENT, COMPLIANCE, AND REGULATORY REPORTING
    • 8.9.1 RISK MANAGEMENT, COMPLIANCE, AND REGULATORY REPORTING TO HELP MAP DATA FLOWS, RELATIONSHIPS, AND CONTROLS TO IDENTIFY VULNERABILITIES AND ENSURE COMPLIANCE
  • 8.10 MARKET & CUSTOMER INTELLIGENCE AND SALES OPTIMIZATION
    • 8.10.1 NEED TO IDENTIFY TRENDS INFORMING TARGETED MARKETING STRATEGIES TO DRIVE MARKET
  • 8.11 OTHER APPLICATIONS

9 KNOWLEDGE GRAPH MARKET, BY VERTICAL

  • 9.1 INTRODUCTION
    • 9.1.1 VERTICALS: KNOWLEDGE GRAPH MARKET DRIVERS
  • 9.2 BFSI
    • 9.2.1 INCREASING NEED TO MANAGE COMPLEX DATA TO SUPPORT MARKET GROWTH
    • 9.2.2 CASE STUDY
      • 9.2.2.1 Anti-money laundering (AML)
        • 9.2.2.1.1 Major US Financial Institutions enhanced anti-money laundering capabilities with TigerGraph
      • 9.2.2.2 Fraud detection & risk management
        • 9.2.2.2.1 BNP Paribas Personal Finance achieved 20% fraud reduction with Neo4j Graph Database
      • 9.2.2.3 Identity & access management
        • 9.2.2.3.1 Intuit safeguarded data of 100 million customers with Neo4j
      • 9.2.2.4 Risk management
        • 9.2.2.4.1 Global bank enhanced trade surveillance for risk management in BFSI
      • 9.2.2.5 Data integration & governance
        • 9.2.2.5.1 Optimizing data integration and governance for real-time risk management and compliance
      • 9.2.2.6 Operational resilience for bank IT systems
        • 9.2.2.6.1 Basel Institute on Governance enhanced asset recovery and financial intelligence with knowledge graphs for global financial institutions with Onto text 141
      • 9.2.2.7 Regulatory compliance
        • 9.2.2.7.1 Multinational auditing company enhanced regulatory compliance and operational efficiency with knowledge graphs of Ontotext
      • 9.2.2.8 Customer 360° view
        • 9.2.2.8.1 Intuit enhanced security and data protection using Neo4j knowledge graph for customer data
      • 9.2.2.9 Know Your Customer (KYC) processes
        • 9.2.2.9.1 AI-powered knowledge graphs streamlined KYC compliance and adverse media analysis in financial services
      • 9.2.2.10 Market analysis and trend detection
        • 9.2.2.10.1 Leading investment bank enhanced investment insights through comprehensive company knowledge graph
      • 9.2.2.11 Policy impact analysis
        • 9.2.2.11.1 Delinian enhanced content production and analysis with semantic publishing platform
      • 9.2.2.12 Customer support
        • 9.2.2.12.1 Banks and insurance companies improved AI-powered knowledge graphs to revolutionize customer support in BFSI
      • 9.2.2.13 Self-service data & digital asset discovery and data integration & governance
        • 9.2.2.13.1 HSBC revolutionized data governance with knowledge graphs in BFSI
  • 9.3 RETAIL & ECOMMERCE
    • 9.3.1 NEED TO OPTIMIZE INVENTORY MANAGEMENT FACILITATED BY KNOWLEDGE GRAPHS TO DRIVE MARKET
    • 9.3.2 CASE STUDY
      • 9.3.2.1 Fraud detection in eCommerce
        • 9.3.2.1.1 PayPal enhanced fraud detection with knowledge graphs
      • 9.3.2.2 Dynamic pricing optimization
        • 9.3.2.2.1 Belgian company revolutionized new product development with food pairing knowledge graph
      • 9.3.2.3 Personalized recommendations
        • 9.3.2.3.1 Xandr created industry-leading identity graph for personalized advertising with TigerGraph
      • 9.3.2.4 Market basket analysis
        • 9.3.2.4.1 eCommerce giants boosted retail sales with knowledge graph-powered market basket analysis
      • 9.3.2.5 Customer experience enhancement
        • 9.3.2.5.1 Retailers improved store operations and increased customer satisfaction using TigerGraph
        • 9.3.2.5.2 Edamam enhanced food knowledge and user experience with knowledge graphs
      • 9.3.2.6 Social media influence on buying behavior
        • 9.3.2.6.1 Leveraging knowledge graphs to track social media influence on buying behavior at Coca-Cola
      • 9.3.2.7 Churn prediction & prevention
        • 9.3.2.7.1 Reduction of customer churn with knowledge graphs
      • 9.3.2.8 Product configuration & recommendation
        • 9.3.2.8.1 Leading automotive manufacturer personalized customer experience with knowledge graphs for product configuration
      • 9.3.2.9 Customer segmentation & targeting
        • 9.3.2.9.1 Xbox enhanced user experience with TigerGraph for better customer insights and loyalty
      • 9.3.2.10 Customer 360° view
        • 9.3.2.10.1 Technology giant enhanced customer engagement with TigerGraph for personalized experiences
      • 9.3.2.11 Review & reputation management
        • 9.3.2.11.1 Neo4j managed brand reputation with knowledge graphs at TripAdvisor
      • 9.3.2.12 Customer support
        • 9.3.2.12.1 Retailer enhanced operations and customer satisfaction with TigerGraph for root cause analysis
  • 9.4 HEALTHCARE, LIFE SCIENCES, AND PHARMACEUTICALS
    • 9.4.1 NEED TO REVOLUTIONIZE HEALTHCARE PRACTICES TO PROPEL ADOPTION OF KNOWLEDGE GRAPHS
    • 9.4.2 CASE STUDY
      • 9.4.2.1 Drug discovery & development
        • 9.4.2.1.1 Early Drug R&D center accelerated cancer research with Ontotext's target discovery
        • 9.4.2.1.2 Ontotext's Target Discovery accelerated Alzheimer's breakthroughs with knowledge graphs
      • 9.4.2.2 Clinical trial management
        • 9.4.2.2.1 NuMedii streamlined clinical trial management with AI-powered knowledge graphs with Ontotext
      • 9.4.2.3 Medical claim processing
        • 9.4.2.3.1 UnitedHealth Group revolutionized medical claim processing with TigerGraph
      • 9.4.2.4 Clinical intelligence
        • 9.4.2.4.1 Leading US Children's Hospital gained deeper insights into impact of its faculty research
      • 9.4.2.5 Healthcare provider network analysis
        • 9.4.2.5.1 Amgen improved quality of healthcare by identifying influencers and referral networks using TigerGraph
      • 9.4.2.6 Customer support
        • 9.4.2.6.1 Exact Sciences Corporation revolutionized customer support in healthcare with a knowledge graph-powered 360° View
      • 9.4.2.7 Patient journey & care pathway analysis
        • 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
        • 9.4.2.8.1 Boehringer Ingelheim accelerating pharmaceutical innovation with Stardog Knowledge Graph
  • 9.5 TELECOM & TECHNOLOGY
    • 9.5.1 NEED TO OPTIMIZE INTRICATE NETWORK INFRASTRUCTURE AND CUSTOMIZED SERVICE OFFERINGS TO FUEL MARKET GROWTH
    • 9.5.2 CASE STUDY
      • 9.5.2.1 Network optimization & management
        • 9.5.2.1.1 Cyber resilience leader scaled next-generation cybersecurity with TigerGraph to combat evolving threats
      • 9.5.2.2 Network security analysis
        • 9.5.2.2.1 Multinational cybersecurity and defense company accelerated risk identification in cybersecurity with knowledge graphs with Ontotext
      • 9.5.2.3 Identity & access management
        • 9.5.2.3.1 Technology giant improved customer experiences with TigerGraph
      • 9.5.2.4 IT asset management
        • 9.5.2.4.1 Orange used Thing'in to build digital twin platform
      • 9.5.2.5 IoT device management & connectivity
        • 9.5.2.5.1 AWS enhanced IoT device management with Amazon Neptune's scalable graph database solutions
      • 9.5.2.6 Metadata enrichment
        • 9.5.2.6.1 Cisco utilized Neo4j to enhance and assign metadata to its vast document collection
      • 9.5.2.7 Data integration & governance
        • 9.5.2.7.1 Dun & Bradstreet enhanced compliance with Neo4j's graph technology
      • 9.5.2.8 Self-service data & digital asset discovery
        • 9.5.2.8.1 Telecom provider optimized telecom operations with Neo4j's self-service data and digital asset discovery
      • 9.5.2.9 Service incident management
        • 9.5.2.9.1 BT Group revolutionizing telecom inventory management with Neo4j knowledge graph
  • 9.6 GOVERNMENT
    • 9.6.1 SPEEDY DATA INTEGRATION AND INTEROPERABILITY TO BOOST MARKET GROWTH
    • 9.6.2 CASE STUDY
      • 9.6.2.1 Government service optimization
        • 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
      • 9.6.2.2 Legislative & regulatory analysis
        • 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
        • 9.6.2.3.1 Knowledge graphs enhanced crisis response for real-time decision-making
      • 9.6.2.4 Environmental impact analysis and ESG
        • 9.6.2.4.1 Vienna University of Technology transformed architectural design with ECOLOPES knowledge graph
      • 9.6.2.5 Social network analysis for security & law enforcement
        • 9.6.2.5.1 Social Network Analysis strengthened security via knowledge graphs
      • 9.6.2.6 Policy Impact Analysis
        • 9.6.2.6.1 Governments leveraged knowledge graphs for effective policy impact analysis
      • 9.6.2.7 Knowledge management
        • 9.6.2.7.1 Ellas leveraged Graphdb's knowledge graphs to bridge gender gaps in STEM leadership
      • 9.6.2.8 Data integration & governance
        • 9.6.2.8.1 Government agency took digital and print library services to next level partnering with metaphacts and Ontotext
  • 9.7 MANUFACTURING & AUTOMOTIVE
    • 9.7.1 EASY PREDICTIVE MAINTENANCE AND DECREASE IN DOWNTIME TO SUPPORT MARKET GROWTH
    • 9.7.2 CASE STUDY
      • 9.7.2.1 Equipment maintenance and predictive maintenance
        • 9.7.2.1.1 Ford Motor Company enhanced production efficiency with TigerGraph for predictive maintenance
      • 9.7.2.2 Product lifecycle management
        • 9.7.2.2.1 Leading European manufacturer of electrical components enhanced product discoverability through semantic knowledge graphs
      • 9.7.2.3 Manufacturing process optimization
        • 9.7.2.3.1 Production streamlined efficiency with knowledge graphs
      • 9.7.2.4 Enhance vehicle safety & reliability
        • 9.7.2.4.1 Knowledge graphs improved vehicle safety with predictive maintenance
      • 9.7.2.5 Optimization of industrial processes
        • 9.7.2.5.1 Leading manufacturer of Building Automation Systems (BAS) graphs improved vehicle safety with Ontotext's GraphDB
      • 9.7.2.6 Root cause analysis
        • 9.7.2.6.1 Root Cause Analysis uncovered process failures with using knowledge graphs
      • 9.7.2.7 Inventory management & demand forecasting
        • 9.7.2.7.1 Knowledge graphs optimized inventory and demand forecasting with knowledge graphs
      • 9.7.2.8 Service incident management
        • 9.7.2.8.1 Knowledge graphs accelerated service incident resolution with knowledge graphs
      • 9.7.2.9 Staff & resource allocation
        • 9.7.2.9.1 Knowledge graphs optimized staff and resource allocation with knowledge graphs
      • 9.7.2.10 Product configuration & recommendation
        • 9.7.2.10.1 Leading Building Automation Systems (BAS) manufacturers used Brick schema to represent BAS components and their complex interactions
  • 9.8 MEDIA & ENTERTAINMENT
    • 9.8.1 NEED TO IMPROVE CONTENT MANAGEMENT PROCEDURES AND BETTER DATA-DRIVEN DECISIONS TO FOSTER MARKET GROWTH
    • 9.8.2 CASE STUDY
      • 9.8.2.1 Content recommendation & personalization
        • 9.8.2.1.1 Leading television broadcaster streamlined data management and improved search efficiency with knowledge graphs
      • 9.8.2.2 Audience segmentation & targeting
        • 9.8.2.2.1 KT Corporation enhanced IPTV Content Discovery with semantic search for better audience targeting
      • 9.8.2.3 Social media influence analysis
        • 9.8.2.3.1 Myntelligence used TigerGraph's advanced graph analytics to analyze relationships and interactions
      • 9.8.2.4 Copyright & licensing management
        • 9.8.2.4.1 British Museum and Europeana leveraged knowledge graphs for efficient content management and licensing in cultural heritage
      • 9.8.2.5 Self-service data & digital asset discovery
        • 9.8.2.5.1 BBC transformed content management with semantic publishing for enhanced user experience
      • 9.8.2.6 Content recommendation systems
        • 9.8.2.6.1 STM publisher leveraged knowledge platform for enhanced content recommendation
      • 9.8.2.7 User engagement analysis
        • 9.8.2.7.1 Bulgarian media company leveraged Ontotext's knowledge graphs for enhanced user engagement and ad targeting
      • 9.8.2.8 Knowledge management
        • 9.8.2.8.1 Rappler empowered transparent elections with first Philippine Politics Knowledge Graph
        • 9.8.2.8.2 Perfect Memory and Ontotext developed custom data program platform based on knowledge graph solution to streamline data management
  • 9.9 ENERGY, UTILITIES, AND INFRASTRUCTURE
    • 9.9.1 DEVELOPMENT OF INNOVATIVE TECHNOLOGIES TO DRIVE DEMAND FOR KNOWLEDGE GRAPH SOLUTIONS
    • 9.9.2 CASE STUDY
      • 9.9.2.1 Grid management
        • 9.9.2.1.1 Transmission Systems Operator (TSO) modernized asset management with knowledge graphs for enhanced grid reliability
      • 9.9.2.2 Energy trading optimization
        • 9.9.2.2.1 Global energy and commodities markets information provider gained enhanced operational efficiencies with semantic information extraction
      • 9.9.2.3 Renewable energy integration & optimization
        • 9.9.2.3.1 State Grid Corporation of China created speedy energy management system with assistance of TigerGraph
      • 9.9.2.4 Public infrastructure management
        • 9.9.2.4.1 Knowledge graphs enhanced infrastructure management for better decision-making
      • 9.9.2.5 Customer engagement & billing
        • 9.9.2.5.1 Knowledge graphs streamlined customer engagement and billing
      • 9.9.2.6 Environmental impact analysis & ESG
        • 9.9.2.6.1 Improved environmental impact analysis with knowledge graphs for ESG reporting
      • 9.9.2.7 Service incident management
        • 9.9.2.7.1 Enxchange transformed service incident management in energy with graph-based digital twins
      • 9.9.2.8 Staff & resource allocation
        • 9.9.2.8.1 Knowledge graphs optimized staff and resource allocation for efficient operations
      • 9.9.2.9 Railway asset management
        • 9.9.2.9.1 Railway asset management with graph databases enhanced connectivity and efficiency
  • 9.10 TRAVEL & HOSPITALITY
    • 9.10.1 NEED FOR KNOWLEDGE GRAPHS TO HELP DEVELOP INNOVATIVE TECHNOLOGIES TO DRIVE MARKET
    • 9.10.2 CASE STUDY
      • 9.10.2.1 Personalized travel recommendations
        • 9.10.2.1.1 Travel personalization with knowledge graphs for tailored recommendations
      • 9.10.2.2 Dynamic pricing optimization
        • 9.10.2.2.1 Marriott International implemented knowledge graph technology for dynamic pricing and revenue optimization
      • 9.10.2.3 Customer journey mapping
        • 9.10.2.3.1 Knowledge graphs mapped customer journey for enhanced travel experiences
      • 9.10.2.4 Booking & reservation optimization
        • 9.10.2.4.1 WestJet Airlines transformed flight scheduling into a seamless, customer-friendly experience with Neo4j
      • 9.10.2.5 Customer experience enhancement
        • 9.10.2.5.1 Airbnb transformed customer experience with unified data and actionable insights with Neo4j graph database
      • 9.10.2.6 Product configuration and recommendation
        • 9.10.2.6.1 Knowledge graphs streamlined product configuration and recommendations
  • 9.11 TRANSPORTATION & LOGISTICS
    • 9.11.1 NEED FOR DEVELOPMENT OF INNOVATIVE TECHNOLOGIES TO BOLSTER MARKET GROWTH
    • 9.11.2 CASE STUDY
      • 9.11.2.1 Route optimization & fleet management
        • 9.11.2.1.1 Transport for London (TfL) optimized route management and incident response with digital twin
      • 9.11.2.2 Supply chain visibility
        • 9.11.2.2.1 Knowledge graphs enhanced supply chain visibility with real-time insights
      • 9.11.2.3 Equipment maintenance & predictive maintenance
        • 9.11.2.3.1 Knowledge graphs optimized equipment maintenance with predictive insights via knowledge graphs
      • 9.11.2.4 Supply chain management
        • 9.11.2.4.1 Knowledge graphs streamlined supply chain management for better coordination
      • 9.11.2.5 Vendor & supplier analysis
        • 9.11.2.5.1 Vendor and supplier analysis with knowledge graphs for smarter sourcing
      • 9.11.2.6 Operational efficiency & decision making
        • 9.11.2.6.1 Careem improved operational efficiency through fraud detection
  • 9.12 OTHER VERTICALS

10 KNOWLEDGE GRAPH MARKET, BY REGION

  • 10.1 INTRODUCTION
  • 10.2 NORTH AMERICA
    • 10.2.1 NORTH AMERICA: MACROECONOMIC OUTLOOK
    • 10.2.2 US
      • 10.2.2.1 Increasing need for structured data analytics and interoperability to drive market
    • 10.2.3 CANADA
      • 10.2.3.1 Increasing complexity of data and demand for efficient data to propel market
  • 10.3 EUROPE
    • 10.3.1 EUROPE: MACROECONOMIC OUTLOOK
    • 10.3.2 UK
      • 10.3.2.1 Increasing complexity of data and demand for advanced data integration solutions to fuel market growth
    • 10.3.3 GERMANY
      • 10.3.3.1 Focus on Industry 4.0 to drive demand for knowledge graph
    • 10.3.4 FRANCE
      • 10.3.4.1 Focus on technological innovation, robust digital infrastructure, and supportive regulatory environment to foster market growth
    • 10.3.5 ITALY
      • 10.3.5.1 Increasing adoption of semantic technologies and government commitment to fostering innovation to drive market
    • 10.3.6 SPAIN
      • 10.3.6.1 Strategic initiatives in AI development sector and implementation of Spain's 2024 Artificial Intelligence Strategy to accelerate market
    • 10.3.7 NORDIC COUNTRIES
      • 10.3.7.1 High digital literacy, advanced AI readiness, and robust public-private partnerships to bolster market growth
    • 10.3.8 REST OF EUROPE
  • 10.4 ASIA PACIFIC
    • 10.4.1 ASIA PACIFIC: MACROECONOMIC OUTLOOK
    • 10.4.2 CHINA
      • 10.4.2.1 Rapid technological advancements, government initiatives, and strategic focus on integrating AI to boost market
    • 10.4.3 JAPAN
      • 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
    • 10.4.4 INDIA
      • 10.4.4.1 Focus on promoting advanced technology usage through government initiatives to foster market growth
    • 10.4.5 SOUTH KOREA
      • 10.4.5.1 Strong focus on developing and enhancing public-private partnerships to drive market
    • 10.4.6 AUSTRALIA & NEW ZEALAND
      • 10.4.6.1 Strategic collaborations for development in new age technologies to drive market
    • 10.4.7 REST OF ASIA PACIFIC
  • 10.5 MIDDLE EAST & AFRICA
    • 10.5.1 MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK
    • 10.5.2 GCC COUNTRIES
      • 10.5.2.1 Increasing investment in AI technologies for development to fuel market growth
      • 10.5.2.2 UAE
        • 10.5.2.2.1 Rising government support for AI and digital transformation initiatives to foster market growth
      • 10.5.2.3 KSA
        • 10.5.2.3.1 Government initiatives and investments in digital infrastructure to propel market
      • 10.5.2.4 Rest of GCC countries
    • 10.5.3 SOUTH AFRICA
      • 10.5.3.1 Growing focus on digital transformation and innovation to accelerate market growth
    • 10.5.4 REST OF MIDDLE EAST & AFRICA 244
  • 10.6 LATIN AMERICA
    • 10.6.1 LATIN AMERICA: MACROECONOMIC OUTLOOK
    • 10.6.2 BRAZIL
      • 10.6.2.1 Increasing demand for personalized customer interactions and advancements in AI technologies to propel market
    • 10.6.3 MEXICO
      • 10.6.3.1 Focus on advancing digital infrastructure to boost market growth
    • 10.6.4 ARGENTINA
      • 10.6.4.1 Focus on digital transformation initiatives to drive market
    • 10.6.5 REST OF LATIN AMERICA

11 COMPETITIVE LANDSCAPE

  • 11.1 INTRODUCTION
  • 11.2 KEY PLAYER STRATEGIES/RIGHT TO WIN
  • 11.3 REVENUE ANALYSIS
  • 11.4 MARKET SHARE ANALYSIS
  • 11.5 MARKET RANKING ANALYSIS
  • 11.6 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023
    • 11.6.1 STARS
    • 11.6.2 EMERGING LEADERS
    • 11.6.3 PERVASIVE PLAYERS
    • 11.6.4 PARTICIPANTS
    • 11.6.5 COMPANY FOOTPRINT: KEY PLAYERS, 2024
      • 11.6.5.1 Company footprint
      • 11.6.5.2 Vertical footprint
      • 11.6.5.3 Offering footprint
      • 11.6.5.4 Regional footprint
  • 11.7 COMPANY EVALUATION MATRIX: START-UPS/SMES, 2024
    • 11.7.1 PROGRESSIVE COMPANIES
    • 11.7.2 RESPONSIVE COMPANIES
    • 11.7.3 DYNAMIC COMPANIES
    • 11.7.4 STARTING BLOCKS
    • 11.7.5 COMPETITIVE BENCHMARKING: START-UPS/SMES, 2024
      • 11.7.5.1 Key start-ups/SMEs
      • 11.7.5.2 Competitive benchmarking of key start-ups/SMEs
  • 11.8 COMPETITIVE SCENARIOS AND TRENDS
    • 11.8.1 PRODUCT LAUNCHES & ENHANCEMENTS
    • 11.8.2 DEALS
  • 11.9 BRAND/PRODUCT COMPARISON
  • 11.10 COMPANY VALUATION AND FINANCIAL METRICS OF KEY KNOWLEDGE GRAPH SOLUTION PROVIDERS 275

12 COMPANY PROFILES

  • 12.1 KEY PLAYERS
    • 12.1.1 NEO4J
      • 12.1.1.1 Business overview
      • 12.1.1.2 Products/Solutions/Services offered
      • 12.1.1.3 Recent developments
        • 12.1.1.3.1 Product enhancements
        • 12.1.1.3.2 Deals
      • 12.1.1.4 MnM view
        • 12.1.1.4.1 Right to win
        • 12.1.1.4.2 Strategic choices
        • 12.1.1.4.3 Weaknesses and competitive threats
    • 12.1.2 AMAZON WEB SERVICES, INC
      • 12.1.2.1 Business overview
      • 12.1.2.2 Products/Solutions/Services offered
      • 12.1.2.3 Recent developments
        • 12.1.2.3.1 Product enhancements
      • 12.1.2.4 MnM view
        • 12.1.2.4.1 Right to win
        • 12.1.2.4.2 Strategic choices
        • 12.1.2.4.3 Weaknesses and competitive threats
    • 12.1.3 TIGERGRAPH
      • 12.1.3.1 Business overview
      • 12.1.3.2 Products/Solutions/Services offered
      • 12.1.3.3 Recent developments
        • 12.1.3.3.1 Product enhancements
        • 12.1.3.3.2 Deals
      • 12.1.3.4 MnM view
        • 12.1.3.4.1 Right to win
        • 12.1.3.4.2 Strategic choices
        • 12.1.3.4.3 Weaknesses and competitive threats
    • 12.1.4 GRAPHWISE
      • 12.1.4.1 Business overview
      • 12.1.4.2 Products/Solutions/Services offered
      • 12.1.4.3 Recent developments
        • 12.1.4.3.1 Product enhancements
      • 12.1.4.4 MnM view
        • 12.1.4.4.1 Right to win
        • 12.1.4.4.2 Strategic choices
        • 12.1.4.4.3 Weaknesses and competitive threats 287
    • 12.1.5 RELATIONALAI
      • 12.1.5.1 Business overview
      • 12.1.5.2 Products/Solutions/Services offered
      • 12.1.5.3 Recent developments
        • 12.1.5.3.1 Product launches
      • 12.1.5.4 MnM view
        • 12.1.5.4.1 Right to win
        • 12.1.5.4.2 Strategic choices
        • 12.1.5.4.3 Weaknesses and competitive threats
    • 12.1.6 IBM
      • 12.1.6.1 Business overview
      • 12.1.6.2 Products/Solutions/Services offered
      • 12.1.6.3 Recent developments
        • 12.1.6.3.1 Product enhancements
        • 12.1.6.3.2 Deals
    • 12.1.7 MICROSOFT
      • 12.1.7.1 Business overview
      • 12.1.7.2 Products/Solutions/Services offered
      • 12.1.7.3 Recent developments
        • 12.1.7.3.1 Product enhancements
        • 12.1.7.3.2 Deals
    • 12.1.8 SAP
      • 12.1.8.1 Business overview
      • 12.1.8.2 Products/Solutions/Services offered
      • 12.1.8.3 Recent developments
        • 12.1.8.3.1 Product enhancements
    • 12.1.9 ORACLE
      • 12.1.9.1 Business overview
      • 12.1.9.2 Products/Solutions/Services offered
      • 12.1.9.3 Recent developments
        • 12.1.9.3.1 Product enhancements
    • 12.1.10 STARDOG
      • 12.1.10.1 Business overview
      • 12.1.10.2 Products/Solutions/Services offered
      • 12.1.10.3 Recent developments
        • 12.1.10.3.1 Product enhancements
        • 12.1.10.3.2 Deals 305
    • 12.1.11 ONTOTEXT
      • 12.1.11.1 Business overview
      • 12.1.11.2 Products/Solutions/Services offered
      • 12.1.11.3 Recent developments
        • 12.1.11.3.1 Product enhancements
        • 12.1.11.3.2 Deals
    • 12.1.12 FRANZ INC.
      • 12.1.12.1 Business overview
      • 12.1.12.2 Products/Solutions/Services offered
      • 12.1.12.3 Recent developments
        • 12.1.12.3.1 Product enhancements
    • 12.1.13 ALTAIR
      • 12.1.13.1 Business overview
      • 12.1.13.2 Products/Solutions/Services offered
      • 12.1.13.3 Recent developments
        • 12.1.13.3.1 Product enhancements
        • 12.1.13.3.2 Deals
    • 12.1.14 PROGRESS SOFTWARE CORPORATION
    • 12.1.15 ESRI
    • 12.1.16 SEMANTIC WEB COMPANY
    • 12.1.17 OPENLINK SOFTWARE
  • 12.2 SMES/START-UPS
    • 12.2.1 DATAVID
    • 12.2.2 GRAPHBASE
    • 12.2.3 CONVERSIGHT
    • 12.2.4 ECCENCA
    • 12.2.5 ARANGODB
    • 12.2.6 FLUREE
    • 12.2.7 DIFFBOT
    • 12.2.8 BITNINE
    • 12.2.9 MEMGRAPH
    • 12.2.10 GRAPHAWARE
    • 12.2.11 ONLIM
    • 12.2.12 SMABBLER
    • 12.2.13 WISECUBE
    • 12.2.14 METAPHACTS

13 ADJACENT/RELATED MARKETS

  • 13.1 INTRODUCTION
    • 13.1.1 LIMITATIONS
  • 13.2 GRAPH DATABASE MARKET - GLOBAL FORECAST TO 2030
    • 13.2.1 MARKET DEFINITION
    • 13.2.2 MARKET OVERVIEW
      • 13.2.2.1 Graph database market, by offering
      • 13.2.2.2 Graph database market, by model type
      • 13.2.2.3 Graph database market, by application
      • 13.2.2.4 Graph database market, by vertical
      • 13.2.2.5 Graph database market, by region
  • 13.3 ENTERPRISE CONTENT MANAGEMENT MARKET - GLOBAL FORECAST TO 2029
    • 13.3.1 MARKET DEFINITION
    • 13.3.2 MARKET OVERVIEW
      • 13.3.2.1 Enterprise content management market, by offering
      • 13.3.2.2 Enterprise content management market, by business function
      • 13.3.2.3 Enterprise content management market, by deployment mode
      • 13.3.2.4 Enterprise content management market, by organization size
      • 13.3.2.5 Enterprise content management market, by vertical
      • 13.3.2.6 Enterprise content management market, by region
  • 13.4 GENERATIVE AI MARKET - GLOBAL FORECAST TO 2030
    • 13.4.1 MARKET DEFINITION
    • 13.4.2 MARKET OVERVIEW
      • 13.4.2.1 Generative AI market, by offering
      • 13.4.2.2 Generative AI market, by data modality
      • 13.4.2.3 Generative AI market, by application
      • 13.4.2.4 Generative AI market, by end user
      • 13.4.2.5 Generative AI market, by region

14 APPENDIX

  • 14.1 DISCUSSION GUIDE
  • 14.2 KNOWLEDGESTORE: MARKETSANDMARKETS' SUBSCRIPTION PORTAL
  • 14.3 CUSTOMIZATION OPTIONS
  • 14.4 RELATED REPORTS
  • 14.5 AUTHOR DETAILS

List of Tables

  • TABLE 1 USD EXCHANGE RATE, 2021-2023
  • TABLE 2 RISK ASSESSMENT
  • TABLE 3 AVERAGE SELLING PRICE OF KNOWLEDGE GRAPH SOLUTIONS, BY COUNTRY, 2023
  • TABLE 4 INDICATIVE PRICING ANALYSIS OF KEY PLAYERS
  • TABLE 5 KNOWLEDGE GRAPH MARKET: ECOSYSTEM
  • TABLE 6 LIST OF MAJOR PATENTS
  • TABLE 7 KNOWLEDGE GRAPH MARKET: CONFERENCES AND EVENTS, 2024-2025
  • TABLE 8 NORTH AMERICA: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • TABLE 9 EUROPE: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • TABLE 10 ASIA PACIFIC: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • TABLE 11 REST OF THE WORLD: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • TABLE 12 IMPACT OF PORTER'S FIVE FORCES ON KNOWLEDGE GRAPH MARKET
  • TABLE 13 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE VERTICALS (%)
  • TABLE 14 KEY BUYING CRITERIA FOR TOP THREE VERTICALS
  • TABLE 15 KNOWLEDGE GRAPH MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 16 KNOWLEDGE GRAPH MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 17 KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 18 KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 19 SOLUTIONS: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 20 SOLUTIONS: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 21 ENTERPRISE KNOWLEDGE GRAPH PLATFORMS: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 22 ENTERPRISE KNOWLEDGE GRAPH PLATFORMS: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 23 GRAPH DATABASE ENGINES: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 24 GRAPH DATABASE ENGINES: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 25 KNOWLEDGE MANAGEMENT TOOLSETS: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 26 KNOWLEDGE MANAGEMENT TOOLSETS: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 27 KNOWLEDGE GRAPH MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 28 KNOWLEDGE GRAPH MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 29 SERVICES: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 30 SERVICES: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 31 PROFESSIONAL SERVICES: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 32 PROFESSIONAL SERVICES: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 33 MANAGED SERVICES: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 34 MANAGED SERVICES: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 35 KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 36 KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 37 RESOURCE DESCRIPTION FRAMEWORK (RDF) TRIPLE STORES: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 38 RESOURCE DESCRIPTION FRAMEWORK (RDF) TRIPLE STORES: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 39 LABELED PROPERTY GRAPH (LPG): KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 40 LABELED PROPERTY GRAPH (LPG): KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 41 KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2019-2023 (USD MILLION)
  • TABLE 42 KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2024-2030 (USD MILLION)
  • TABLE 43 DATA GOVERNANCE & MASTER DATA MANAGEMENT: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 44 DATA GOVERNANCE & MASTER DATA MANAGEMENT: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 45 DATA ANALYTICS & BUSINESS INTELLIGENCE: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 46 DATA ANALYTICS & BUSINESS INTELLIGENCE: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 47 KNOWLEDGE & CONTENT MANAGEMENT: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 48 KNOWLEDGE & CONTENT MANAGEMENT: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 49 VIRTUAL ASSISTANTS, SELF-SERVICE DATA, AND DIGITAL ASSET DISCOVERY: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 50 VIRTUAL ASSISTANTS, SELF-SERVICE DATA, AND DIGITAL ASSET DISCOVERY: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 51 PRODUCT & CONFIGURATION MANAGEMENT: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 52 PRODUCT & CONFIGURATION MANAGEMENT: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 53 INFRASTRUCTURE & ASSET MANAGEMENT: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 54 INFRASTRUCTURE & ASSET MANAGEMENT: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 55 PROCESS OPTIMIZATION & RESOURCE MANAGEMENT: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 56 PROCESS OPTIMIZATION & RESOURCE MANAGEMENT: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 57 RISK MANAGEMENT, COMPLIANCE, AND REGULATORY REPORTING: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 58 RISK MANAGEMENT, COMPLIANCE, AND REGULATORY REPORTING: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 59 MARKET & CUSTOMER INTELLIGENCE AND SALES OPTIMIZATION: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 60 MARKET & CUSTOMER INTELLIGENCE AND SALES OPTIMIZATION: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 61 OTHER APPLICATIONS: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 62 OTHER APPLICATIONS: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 63 KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2019-2023 (USD MILLION)
  • TABLE 64 KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2024-2030 (USD MILLION)
  • TABLE 65 BFSI: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 66 BFSI: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 67 RETAIL & ECOMMERCE: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 68 RETAIL & ECOMMERCE: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 69 HEALTHCARE, LIFE SCIENCES, AND PHARMACEUTICALS: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 70 HEALTHCARE, LIFE SCIENCES, AND PHARMACEUTICALS: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 71 TELECOM & TECHNOLOGY: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 72 TELECOM & TECHNOLOGY: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 73 GOVERNMENT: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 74 GOVERNMENT: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 75 MANUFACTURING & AUTOMOTIVE: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 76 MANUFACTURING & AUTOMOTIVE: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 77 MEDIA & ENTERTAINMENT: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 78 MEDIA & ENTERTAINMENT: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 79 ENERGY, UTILITIES, AND INFRASTRUCTURE: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 80 ENERGY, UTILITIES, AND INFRASTRUCTURE: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 81 TRAVEL & HOSPITALITY: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 82 TRAVEL & HOSPITALITY: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 83 TRANSPORTATION & LOGISTICS: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 84 TRANSPORTATION & LOGISTICS: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 85 OTHER VERTICALS: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 86 OTHER VERTICALS: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 87 KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 88 KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 89 NORTH AMERICA: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 90 NORTH AMERICA: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 91 NORTH AMERICA: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 92 NORTH AMERICA: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 93 NORTH AMERICA: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 94 NORTH AMERICA: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 95 NORTH AMERICA: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 96 NORTH AMERICA: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 97 NORTH AMERICA: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2019-2023 (USD MILLION)
  • TABLE 98 NORTH AMERICA: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2024-2030 (USD MILLION)
  • TABLE 99 NORTH AMERICA: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2019-2023 (USD MILLION)
  • TABLE 100 NORTH AMERICA: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2024-2030 (USD MILLION)
  • TABLE 101 NORTH AMERICA: KNOWLEDGE GRAPH MARKET, BY COUNTRY, 2019-2023 (USD MILLION)
  • TABLE 102 NORTH AMERICA: KNOWLEDGE GRAPH MARKET, BY COUNTRY, 2024-2030 (USD MILLION)
  • TABLE 103 US: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 104 US: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 105 US: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 106 US: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 107 US: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 108 US: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 109 US: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 110 US: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 111 US: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2019-2023 (USD MILLION)
  • TABLE 112 US: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2024-2030 (USD MILLION)
  • TABLE 113 US: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2019-2023 (USD MILLION)
  • TABLE 114 US: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2024-2030 (USD MILLION)
  • TABLE 115 EUROPE: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 116 EUROPE: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 117 EUROPE: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 118 EUROPE: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 119 EUROPE: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 120 EUROPE: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 121 EUROPE: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 122 EUROPE: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 123 EUROPE: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2019-2023 (USD MILLION)
  • TABLE 124 EUROPE: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2024-2030 (USD MILLION)
  • TABLE 125 EUROPE: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2019-2023 (USD MILLION)
  • TABLE 126 EUROPE: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2024-2030 (USD MILLION)
  • TABLE 127 EUROPE: KNOWLEDGE GRAPH MARKET, BY COUNTRY, 2019-2023 (USD MILLION)
  • TABLE 128 EUROPE: KNOWLEDGE GRAPH MARKET, BY COUNTRY, 2024-2030 (USD MILLION)
  • TABLE 129 UK: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 130 UK: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 131 UK: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 132 UK: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 133 UK: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 134 UK: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 135 UK: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 136 UK: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 137 UK: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2019-2023 (USD MILLION)
  • TABLE 138 UK: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2024-2030 (USD MILLION)
  • TABLE 139 UK: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2019-2023 (USD MILLION)
  • TABLE 140 UK: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2024-2030 (USD MILLION)
  • TABLE 141 ITALY: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 142 ITALY: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 143 ITALY: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 144 ITALY: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 145 ITALY: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 146 ITALY: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 147 ITALY: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 148 ITALY: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 149 ITALY: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2019-2023 (USD MILLION)
  • TABLE 150 ITALY: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2024-2030 (USD MILLION)
  • TABLE 151 ITALY: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2019-2023 (USD MILLION)
  • TABLE 152 ITALY: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2024-2030 (USD MILLION)
  • TABLE 153 ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 154 ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 155 ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 156 ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 157 ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 158 ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 159 ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 160 ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 161 ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2019-2023 (USD MILLION)
  • TABLE 162 ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2024-2030 (USD MILLION)
  • TABLE 163 ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2019-2023 (USD MILLION)
  • TABLE 164 ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2024-2030 (USD MILLION)
  • TABLE 165 ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY COUNTRY, 2019-2023 (USD MILLION)
  • TABLE 166 ASIA PACIFIC: KNOWLEDGE GRAPH MARKET, BY COUNTRY, 2024-2030 (USD MILLION)
  • TABLE 167 CHINA: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 168 CHINA: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 169 CHINA: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 170 CHINA: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 171 CHINA: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 172 CHINA: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 173 CHINA: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 174 CHINA: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 175 CHINA: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2019-2023 (USD MILLION)
  • TABLE 176 CHINA: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2024-2030 (USD MILLION)
  • TABLE 177 CHINA: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2019-2023 (USD MILLION)
  • TABLE 178 CHINA: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2024-2030 (USD MILLION)
  • TABLE 179 INDIA: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 180 INDIA: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 181 INDIA: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 182 INDIA: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 183 INDIA: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 184 INDIA: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 185 INDIA: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 186 INDIA: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 187 INDIA: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2019-2023 (USD MILLION)
  • TABLE 188 INDIA: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2024-2030 (USD MILLION)
  • TABLE 189 INDIA: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2019-2023 (USD MILLION)
  • TABLE 190 INDIA: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2024-2030 (USD MILLION)
  • TABLE 191 MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 192 MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 193 MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 194 MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 195 MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 196 MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 197 MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 198 MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 199 MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2019-2023 (USD MILLION)
  • TABLE 200 MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2024-2030 (USD MILLION)
  • TABLE 201 MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2019-2023 (USD MILLION)
  • TABLE 202 MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2024-2030 (USD MILLION)
  • TABLE 203 MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 204 MIDDLE EAST & AFRICA: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 205 GCC COUNTRIES: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 206 GCC COUNTRIES: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 207 GCC COUNTRIES: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 208 GCC COUNTRIES: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 209 GCC COUNTRIES: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 210 GCC COUNTRIES: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 211 GCC COUNTRIES: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 212 GCC COUNTRIES: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 213 GCC COUNTRIES: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2019-2023 (USD MILLION)
  • TABLE 214 GCC COUNTRIES: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2024-2030 (USD MILLION)
  • TABLE 215 GCC COUNTRIES: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2019-2023 (USD MILLION)
  • TABLE 216 GCC COUNTRIES: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2024-2030 (USD MILLION)
  • TABLE 217 GCC COUNTRIES: KNOWLEDGE GRAPH MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 218 GCC COUNTRIES: KNOWLEDGE GRAPH MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 219 KSA: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 220 KSA: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 221 KSA: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 222 KSA: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 223 KSA: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 224 KSA: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 225 KSA: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 226 KSA: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 227 KSA: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2019-2023 (USD MILLION)
  • TABLE 228 KSA: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2024-2030 (USD MILLION)
  • TABLE 229 KSA: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2019-2023 (USD MILLION)
  • TABLE 230 KSA: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2024-2030 (USD MILLION)
  • TABLE 231 LATIN AMERICA: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 232 LATIN AMERICA: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 233 LATIN AMERICA: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 234 LATIN AMERICA: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 235 LATIN AMERICA: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 236 LATIN AMERICA: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 237 LATIN AMERICA: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 238 LATIN AMERICA: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 239 LATIN AMERICA: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2019-2023 (USD MILLION)
  • TABLE 240 LATIN AMERICA: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2024-2030 (USD MILLION)
  • TABLE 241 LATIN AMERICA: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2019-2023 (USD MILLION)
  • TABLE 242 LATIN AMERICA: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2024-2030 (USD MILLION)
  • TABLE 243 LATIN AMERICA: KNOWLEDGE GRAPH MARKET, BY COUNTRY, 2019-2023 (USD MILLION)
  • TABLE 244 LATIN AMERICA: KNOWLEDGE GRAPH MARKET, BY COUNTRY, 2024-2030 (USD MILLION)
  • TABLE 245 BRAZIL: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 246 BRAZIL: KNOWLEDGE GRAPH MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 247 BRAZIL: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 248 BRAZIL: KNOWLEDGE GRAPH MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 249 BRAZIL: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 250 BRAZIL: KNOWLEDGE GRAPH MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 251 BRAZIL: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 252 BRAZIL: KNOWLEDGE GRAPH MARKET, BY MODEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 253 BRAZIL: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2019-2023 (USD MILLION)
  • TABLE 254 BRAZIL: KNOWLEDGE GRAPH MARKET, BY APPLICATION, 2024-2030 (USD MILLION)
  • TABLE 255 BRAZIL: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2019-2023 (USD MILLION)
  • TABLE 256 BRAZIL: KNOWLEDGE GRAPH MARKET, BY VERTICAL, 2024-2030 (USD MILLION)
  • TABLE 257 OVERVIEW OF STRATEGIES ADOPTED BY KEY KNOWLEDGE GRAPH MARKET VENDORS
  • TABLE 258 KNOWLEDGE GRAPH MARKET: DEGREE OF COMPETITION
  • TABLE 259 KNOWLEDGE GRAPH MARKET: VERTICAL FOOTPRINT
  • TABLE 260 KNOWLEDGE GRAPH MARKET: OFFERING FOOTPRINT
  • TABLE 261 KNOWLEDGE GRAPH MARKET: REGIONAL FOOTPRINT
  • TABLE 262 KNOWLEDGE GRAPH MARKET: DETAILED LIST OF KEY START-UPS/SMES
  • TABLE 263 KNOWLEDGE GRAPH MARKET: COMPETITIVE BENCHMARKING OF KEY START-UPS/SMES
  • TABLE 264 KNOWLEDGE GRAPH MARKET: PRODUCT LAUNCHES & ENHANCEMENTS, APRIL 2022-DECEMBER 2024
  • TABLE 265 KNOWLEDGE GRAPH MARKET: DEALS, APRIL 2022-DECEMBER 2024
  • TABLE 266 NEO4J: COMPANY OVERVIEW
  • TABLE 267 NEO4J: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 268 NEO4J: PRODUCT ENHANCEMENTS
  • TABLE 269 NEO4J: DEALS
  • TABLE 270 AMAZON WEB SERVICES, INC: COMPANY OVERVIEW
  • TABLE 271 AMAZON WEB SERVICES, INC: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 272 AMAZON WEB SERVICES, INC: PRODUCT ENHANCEMENTS
  • TABLE 273 TIGERGRAPH: COMPANY OVERVIEW
  • TABLE 274 TIGERGRAPH: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 275 TIGERGRAPH: PRODUCT ENHANCEMENTS
  • TABLE 276 TIGERGRAPH: DEALS
  • TABLE 277 GRAPHWISE: COMPANY OVERVIEW
  • TABLE 278 GRAPHWISE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 279 GRAPHWISE: PRODUCT ENHANCEMENTS
  • TABLE 280 RELATIONALAI: COMPANY OVERVIEW
  • TABLE 281 RELATIONALAI: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 282 RELATIONALAI: PRODUCT LAUNCHES
  • TABLE 283 IBM: COMPANY OVERVIEW
  • TABLE 284 IBM: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 285 IBM: PRODUCT ENHANCEMENTS
  • TABLE 286 IBM: DEALS
  • TABLE 287 MICROSOFT: COMPANY OVERVIEW
  • TABLE 288 MICROSOFT: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 289 MICROSOFT: PRODUCT ENHANCEMENTS
  • TABLE 290 MICROSOFT: DEALS
  • TABLE 291 SAP: COMPANY OVERVIEW
  • TABLE 292 SAP: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 293 SAP: PRODUCT ENHANCEMENTS
  • TABLE 294 ORACLE: COMPANY OVERVIEW
  • TABLE 295 ORACLE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 296 ORACLE: PRODUCT ENHANCEMENTS
  • TABLE 297 STARDOG: COMPANY OVERVIEW
  • TABLE 298 STARDOG: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 299 STARDOG: PRODUCT ENHANCEMENTS
  • TABLE 300 STARDOG: DEALS
  • TABLE 301 ONTOTEXT: COMPANY OVERVIEW
  • TABLE 302 ONTOTEXT: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 303 ONTOTEXT: PRODUCT ENHANCEMENTS
  • TABLE 304 ONTOTEXT: DEALS
  • TABLE 305 FRANZ INC.: COMPANY OVERVIEW
  • TABLE 306 FRANZ INC.: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 307 FRANZ INC.: PRODUCT ENHANCEMENTS
  • TABLE 308 ALTAIR: COMPANY OVERVIEW
  • TABLE 309 ALTAIR: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 310 ALTAIR: PRODUCT ENHANCEMENTS
  • TABLE 311 ALTAIR: DEALS
  • TABLE 312 ADJACENT REPORTS
  • TABLE 313 GRAPH DATABASE MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 314 GRAPH DATABASE MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 315 GRAPH DATABASE MARKET, BY MODEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 316 GRAPH DATABASE MARKET, BY MODEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 317 GRAPH DATABASE MARKET, BY APPLICATION, 2019-2023 (USD MILLION)
  • TABLE 318 GRAPH DATABASE MARKET, BY APPLICATION, 2024-2030 (USD MILLION)
  • TABLE 319 GRAPH DATABASE MARKET, BY VERTICAL, 2019-2023 (USD MILLION)
  • TABLE 320 GRAPH DATABASE MARKET, BY VERTICAL, 2024-2030 (USD MILLION)
  • TABLE 321 GRAPH DATABASE MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 322 GRAPH DATABASE MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 323 ENTERPRISE CONTENT MANAGEMENT MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 324 ENTERPRISE CONTENT MANAGEMENT MARKET, BY OFFERING, 2024-2029 (USD MILLION)
  • TABLE 325 ENTERPRISE CONTENT MANAGEMENT MARKET, BY BUSINESS FUNCTION, 2019-2023 (USD MILLION)
  • TABLE 326 ENTERPRISE CONTENT MANAGEMENT MARKET, BY BUSINESS FUNCTION, 2024-2029 (USD MILLION)
  • TABLE 327 ENTERPRISE CONTENT MANAGEMENT MARKET, BY DEPLOYMENT MODE, 2019-2023 (USD MILLION)
  • TABLE 328 ENTERPRISE CONTENT MANAGEMENT MARKET, BY DEPLOYMENT MODE, 2024-2029 (USD MILLION)
  • TABLE 329 ENTERPRISE CONTENT MANAGEMENT MARKET, BY ORGANIZATION SIZE, 2019-2023 (USD MILLION)
  • TABLE 330 ENTERPRISE CONTENT MANAGEMENT MARKET, BY ORGANIZATION SIZE, 2024-2029 (USD MILLION)
  • TABLE 331 ENTERPRISE CONTENT MANAGEMENT MARKET, BY VERTICAL, 2019-2023 (USD MILLION)
  • TABLE 332 ENTERPRISE CONTENT MANAGEMENT MARKET, BY VERTICAL, 2024-2029 (USD MILLION)
  • TABLE 333 ENTERPRISE CONTENT MANAGEMENT MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 334 ENTERPRISE CONTENT MANAGEMENT MARKET, BY REGION, 2024-2029 (USD MILLION)
  • TABLE 335 GENERATIVE AI MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 336 GENERATIVE AI MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 337 GENERATIVE AI MARKET, BY DATA MODALITY, 2019-2023 (USD MILLION)
  • TABLE 338 GENERATIVE AI MARKET, BY DATA MODALITY, 2024-2030 (USD MILLION)
  • TABLE 339 GENERATIVE AI MARKET, BY APPLICATION, 2019-2023 (USD MILLION)
  • TABLE 340 GENERATIVE AI MARKET, BY APPLICATION, 2024-2030 (USD MILLION)
  • TABLE 341 GENERATIVE AI MARKET, BY END USER, 2019-2023 (USD MILLION)
  • TABLE 342 GENERATIVE AI MARKET, BY END USER, 2024-2030 (USD MILLION)
  • TABLE 343 GENERATIVE AI MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 344 GENERATIVE AI MARKET, BY REGION, 2024-2030 (USD MILLION)

List of Figures

  • FIGURE 1 KNOWLEDGE GRAPH MARKET: RESEARCH DESIGN
  • FIGURE 2 TOP-DOWN AND APPROACH
  • FIGURE 3 APPROACH 1 (SUPPLY SIDE): REVENUE OF VENDORS IN KNOWLEDGE GRAPH MARKET
  • FIGURE 4 BOTTOM-UP APPROACH
  • FIGURE 5 DEMAND-SIDE ANALYSIS
  • FIGURE 6 BOTTOM-UP (SUPPLY SIDE) ANALYSIS: COLLECTIVE REVENUE FROM SOLUTIONS/SERVICES OF KNOWLEDGE GRAPH MARKET
  • FIGURE 7 DATA TRIANGULATION
  • FIGURE 8 KNOWLEDGE GRAPH MARKET, 2022-2030 (USD MILLION)
  • FIGURE 9 KNOWLEDGE GRAPH MARKET: REGIONAL SNAPSHOT
  • FIGURE 10 GROWING NEED FOR ADVANCED DATA INTEGRATION, CONTEXTUAL INSIGHTS, AND AI-DRIVEN DECISION-MAKING TO DRIVE KNOWLEDGE GRAPH MARKET
  • FIGURE 11 SOLUTIONS SEGMENT TO ACCOUNT FOR LARGER MARKET SHARE IN 2024
  • FIGURE 12 MANAGED SERVICES SEGMENT TO REGISTER HIGHER CAGR DURING FORECAST PERIOD
  • FIGURE 13 LABELED PROPERTY GRAPH (LPG) TO GROW FASTER DURING FORECAST PERIOD
  • FIGURE 14 DATA ANALYTICS & BUSINESS INTELLIGENCE SEGMENT TO DOMINATE IN 2024
  • FIGURE 15 BFSI SEGMENT TO ACCOUNT FOR MAJOR SHARE IN 2024
  • FIGURE 16 GRAPH DATABASE ENGINE AND PROFESSIONAL SERVICES - DOMINANT SEGMENTS IN 2024
  • FIGURE 17 KNOWLEDGE GRAPH MARKET: DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES
  • FIGURE 18 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
  • FIGURE 19 AVERAGE SELLING PRICE TREND OF KEY PLAYERS, BY COUNTRY, 2023
  • FIGURE 20 KNOWLEDGE GRAPH MARKET: SUPPLY CHAIN ANALYSIS
  • FIGURE 21 KEY PLAYERS IN KNOWLEDGE GRAPH MARKET ECOSYSTEM
  • FIGURE 22 LIST OF MAJOR PATENTS FOR KNOWLEDGE GRAPH
  • FIGURE 23 PORTER'S FIVE FORCES MODEL: KNOWLEDGE GRAPH MARKET
  • FIGURE 24 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE VERTICALS
  • FIGURE 25 KEY BUYING CRITERIA FOR TOP THREE VERTICALS
  • FIGURE 26 EVOLUTION OF KNOWLEDGE GRAPH
  • FIGURE 27 USE CASES OF GENERATIVE AI IN KNOWLEDGE GRAPH
  • FIGURE 28 KNOWLEDGE GRAPH MARKET: INVESTMENT AND FUNDING SCENARIO (USD MILLION)
  • FIGURE 29 SERVICES SEGMENT TO GROW AT HIGHER CAGR DURING FORECAST PERIOD
  • FIGURE 30 ENTERPRISE KNOWLEDGE GRAPH PLATFORM SEGMENT TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
  • FIGURE 31 MANAGED SERVICES SEGMENT TO GROW AT HIGHER CAGR DURING FORECAST PERIOD
  • FIGURE 32 RDF TRIPLE STORES MODEL TYPE TO GROW AT HIGHER CAGR DURING FORECAST PERIOD
  • FIGURE 33 DATA ANALYTICS & BUSINESS INTELLIGENCE SEGMENT TO ACCOUNT FOR LARGEST MARKET DURING FORECAST PERIOD
  • FIGURE 34 HEALTHCARE, LIFE SCIENCES, AND PHARMACEUTICALS SEGMENT TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
  • FIGURE 35 NORTH AMERICA: MARKET SNAPSHOT
  • FIGURE 36 ASIA PACIFIC: MARKET SNAPSHOT
  • FIGURE 37 REVENUE ANALYSIS OF KEY COMPANIES IN PAST 5 YEARS
  • FIGURE 38 SHARE OF LEADING COMPANIES IN KNOWLEDGE GRAPH MARKET, 2024
  • FIGURE 39 MARKET RANKING ANALYSIS OF TOP FIVE PLAYERS
  • FIGURE 40 KNOWLEDGE GRAPH MARKET: COMPANY EVALUATION MATRIX (KEY PLAYERS), 2024
  • FIGURE 41 KNOWLEDGE GRAPH MARKET: COMPANY FOOTPRINT
  • FIGURE 42 KNOWLEDGE GRAPH MARKET: COMPANY EVALUATION MATRIX (START-UPS/SMES), 2024
  • FIGURE 43 BRAND/PRODUCT COMPARISON
  • FIGURE 44 FINANCIAL METRICS OF KEY KNOWLEDGE GRAPH MARKET VENDORS
  • FIGURE 45 COMPANY VALUATION OF KEY KNOWLEDGE GRAPH MARKET VENDORS
  • FIGURE 46 AMAZON WEB SERVICES: COMPANY SNAPSHOT
  • FIGURE 47 IBM: COMPANY SNAPSHOT
  • FIGURE 48 MICROSOFT: COMPANY SNAPSHOT
  • FIGURE 49 SAP: COMPANY SNAPSHOT
  • FIGURE 50 ORACLE: COMPANY SNAPSHOT
  • FIGURE 51 ALTAIR: COMPANY SNAPSHOT