Knowledge Graph Market Size, By Task Type (Link Prediction, Entity Resolution, Link-based Clustering), By Data Source (Structured, Unstructured, Semi-structured), By Organization Size (SMEs, Large Enterprises), Application, Type, End Use, Forecast 2023 – 2032

Knowledge Graph Market Size

Knowledge Graph Market size was valued at USD 1 billion in 2022 and is predicted to register at a CAGR of over 13.5% between 2023 and 2032. The integration of root cause analysis platforms with AI tools and knowledge graphs in monitoring IT environments is driving the market progression. These platforms utilize advanced algorithms and knowledge graphs to efficiently identify and analyze issues in IT systems.
 

For instance, in July 2023, Webb.ai launched an early access for the continuous automated root cause analysis platform. The platform employs a combination of generative AI and machine learning algorithm capabilities derived from Large Language Models (LLMs) to consolidate alerts into advanced insights. These insights are then presented in natural language to DevOps team members.
 

Applications such as search engines, recommendation systems, and data integration are fueling the demand for the market. Search engines utilize knowledge graphs to provide more accurate and relevant search results. Recommendation systems employ these graphs to understand user preferences and deliver personalized content. In data integration, knowledge graphs facilitate the seamless connection of diverse data sources. These applications highlight the versatility and efficiency of knowledge graphs, driving their adoption across various sectors and boosting their market demand.
 

Maintaining high-quality & consistent data poses significant challenges in the knowledge graph market. Integrating information from diverse sources often results in varied data formats and standards. Inaccurate or inconsistent data can lead to flawed analyses and unreliable insights. Ensuring data quality requires meticulous cleansing, transformation, and validation processes. Additionally, as knowledge graphs continually evolve, sustaining data accuracy becomes an ongoing challenge, demanding robust governance frameworks and continuous monitoring to maintain the integrity of the interconnected information within the graph.
 

COVID-19 Impact

The COVID-19 pandemic accelerated the adoption of knowledge graph technologies. With the increased reliance on data-driven decision-making in healthcare and public health sectors, knowledge graphs have played a pivotal role in organizing vast amounts of pandemic-related data. These graphs facilitated rapid analysis, aiding researchers, healthcare professionals, and policymakers in understanding the virus spread, treatment patterns, and vaccine distribution. The pandemic underscored the importance of structured data representation, boosting the demand for knowledge graph solutions.
 

Knowledge Graph Market Trends

The introduction of geospatial knowledge graphs for managing geospatial datasets is driving the market expansion. Advanced graph technologies enhance the organization and utilization of location-based data. For instance, in May 2023, Foursquare, a standalone geospatial technology platform, unveiled its geospatial knowledge graph. This innovative approach helped in organizing geospatial datasets through graph technologies and the H3 grid system, revolutionizing the manner in which businesses extracted value from location data.
 

The growing need for semantic search plays a crucial role in propelling the market demand. Semantic search engines, powered by knowledge graphs, delve beyond simple keyword matches. They understand the context, intent, and relationship between words, providing users with highly relevant & contextually accurate search results. As the volume of online content expands exponentially, businesses and users require more sophisticated and precise search capabilities. Knowledge graphs enable this by adding layers of semantic understanding, making them indispensable for modern search engines and applications.
 

Knowledge Graph Market Analysis

Based on type, the market is divided into context-rich knowledge graphs, external-sensing knowledge graphs, and NLP knowledge graphs. The context-rich knowledge graphs segment is expected to grow at a CAGR of over 12% by 2032. Context-rich knowledge graphs are gaining traction due to their ability to provide an enhanced understanding of data. Unlike traditional knowledge graphs, they incorporate context, allowing for a more nuanced interpretation of relationships and information. This contextual awareness is crucial in scenarios where the meaning of data points depends on specific circumstances. By capturing context, these graphs offer a deeper & more accurate analysis, enabling businesses to extract insights that might otherwise be overlooked, thus driving their adoption across various sectors within the market.

Based on end user, the knowledge graph market is categorized into healthcare, e-commerce & retail, BFSI, government, media & entertainment, manufacturing, transportation & logistics, and others. The BFSI segment was valued at over USD 230 million in 2022. In the BFSI sector, knowledge graphs are driving advancements in fraud detection and prevention. By meticulously organizing vast amounts of data related to customer transactions and behavior, knowledge graphs create detailed customer profiles. These profiles, enriched with transactional data, enable sophisticated fraud detection algorithms. By understanding intricate patterns and relationships, BFSI institutions can swiftly identify and prevent fraudulent activities, ensuring financial security for both the institutions and its customers, making knowledge graphs indispensable in enhancing the sector's security measures.
 

North America led the knowledge graph market with a share of over 35% in 2022. The strategic partnerships to accelerate the migration from varied data sources to valuable data products are significantly propelling the North American market. These collaborations leverage innovative technologies and expertise to streamline data processing, enhance efficiency, and drive insightful decision-making. For instance, in August 2022, Modak Analytics, a prominent data engineering solutions company, and Neo4j, the foremost graph data platform globally, forged a strategic partnership. This collaboration empowered enterprises to expedite the transition from diverse data sources to valuable data products, leveraging the combined capabilities of Modak Nabu and Neo4j.
 

Knowledge Graph Market Share

Major players operating in the knowledge graph industry are:

• AWS
• Cambridge Semantics
• Franz Inc.
• Google
• IBM Corporation
• Microsoft
• Neo4j
• Ontotext
• Oracle
• PoolParty
• Stardog

The market is highly competitive with dominant players such as IBM and Microsoft. Major players focus on R&D, aiming to enhance graph algorithms and data integration technologies. Partnerships and acquisitions also drive market size, fostering a competitive environment.
 

Knowledge Graph Industry News

• In March 2023, Kobai, the no-code knowledge graph platform, introduced Kobai Saturn, the industry's pioneering knowledge graph utilizing the scale, performance, and cost-effectiveness of the lakehouse architecture. Extending the functionalities of the Kobai Platform, Kobai Saturn integrates all use cases and functions into a unified semantic layer, offering enhanced capabilities for seamless data management and analysis.
   

The knowledge graph market research report includes in-depth coverage of the industry with estimates & forecast in terms of revenue (USD Million) from 2018 to 2032, for the following segments:

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By Type, 2018 – 2032

• Context-rich knowledge graphs
• External-sensing knowledge graphs
• NLP knowledge graphs

By Task Type, 2018 – 2032

• Link prediction
• Entity resolution
• Link-based clustering

By Data Source, 2018 – 2032

• Structured data
• Unstructured data
• Semi-structured data

By Organization Size, 2018 – 2032

• SMEs
• Large enterprises

By Application, 2018 – 2032

• Semantic search
• Recommendation systems
• Data integration
• Knowledge management
• AI & machine learning

By End User, 2018 – 2032

• Healthcare
• E-commerce & retail
• BFSI
• Government
• Media & entertainment
• Manufacturing
• Transportation & logistics
• Others

The above information is provided for the following regions and countries:

• North America
  • U.S.
  • Canada
• Europe
  • UK
  • Germany
  • France
  • Italy
  • Spain
  • Nordics
• Asia Pacific
  • China
  • India
  • Japan
  • South Korea
  • Australia
  • Southeast Asia 
• Latin America
  • Brazil
  • Mexico
  • Argentina
• MEA
  • UAE
  • South Africa
  • Saudi Arabia