United States Knowledge Graph Market 2031 | Growth Drivers, Key Players & Investment Opportunities

Market Size and Growth

The Global Knowledge Graph Market reached US$ 0.7 billion in 2022 and is expected to reach US$ 3.6 billion by 2030, growing with a CAGR of 22.1% during the forecast period 2024-2031.

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Key Development:

United States: Recent Knowledge Graph Industry Developments

✅ In December 2025, Atlassian acquired Secoda, a Toronto‐based AI data catalog and semantic knowledge platform, to integrate unified data and contextual insights into its Rovo AI platform, strengthening enterprise knowledge graph capabilities across teams and applications.

✅ In November 2025, Oxford Semantic Technologies announced refreshed leadership and a new U.S. patent for advanced semantic reasoning, boosting its RDFox knowledge graph engine's performance for enterprise applications and signaling future product expansion.

✅ In October 2025, Progress Software launched Agentic RAG, a no‐code RAG‐as‐a‐Service platform leveraging multimodal databases including knowledge graphs to make unstructured data more accessible and actionable for enterprises.

✅ In October 2025, major knowledge graph vendors Neo4j, AWS Neptune, Microsoft Azure Cosmos DB and others expanded graph‐native capabilities across scalable enterprise deployments, with enhancements in analytics, visualization and enterprise integration announced.

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Japan: Recent Knowledge Graph Industry Developments

✅ In October 2025, industry discussions and initiatives emphasized combining knowledge graphs with generative AI for improved reasoning and reduced hallucinations in enterprise systems, driven by Japan‐focused tech communities and research collaborations.

✅ In late 2025, prototype work on real‐time knowledge graphs on edge devices gained visibility, showcasing self‐optimizing graph systems running on compact hardware for real‐time semantic processing and analytics.

✅ In the recent Japan 3D GeoInfo Conference (2025), knowledge graph construction experiments were presented, demonstrating hierarchical graph methods handling large datasets and advanced query prototypes, underscoring academic progress in graph computing.

✅ In May 2025, JSAI2025 hosted a session on synthetic data generation using GANs and LLMs with knowledge graph integration, highlighting advanced research and applications in multi‐domain data synthesis and AI reasoning.

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Key Players:

=> AWS, Cambridge Semantics, Franz Inc., Google, IBM Corporation, Microsoft, Stardog, Neo4j, Ontotext and Oracle.

Key Segments:

By Type

General Knowledge Graphs dominate with 55% share, providing broad contextual insights across multiple domains. Industry Knowledge Graphs account for 45%, tailored for vertical-specific applications such as healthcare, BFSI, and e-commerce.

By Task

Link Prediction leads with 30% share, widely used for discovering hidden relationships in datasets. Entity Resolution contributes 25%, enabling accurate identification of entities across diverse data sources. Link-based Clustering holds 15%, supporting grouping and pattern recognition. Internet-based Tasks account for 10%, while Others make up 20%, including hybrid and emerging tasks like reasoning and inference.

By Data Source

Structured Data holds 40% share, derived from relational databases and enterprise systems. Unstructured Data contributes 35%, sourced from documents, emails, and media. Semi-structured Data accounts for 25%, including XML, JSON, and logs.

By Organization Size

Large Enterprises dominate with 60% share, leveraging knowledge graphs for complex analytics and AI/ML integration. SMEs account for 40%, driven by scalable cloud-based solutions and affordable deployment models.

By Application

Semantic Search leads with 25% share, enhancing information retrieval accuracy. Recommendation Systems account for 20%, widely used in e-commerce and media. Data Integration holds 15%, while Knowledge Management contributes 20%. AI & Machine Learning Applications represent 20%, leveraging knowledge graphs for predictive analytics, NLP, and automated decision-making.

By End-User

Healthcare - 20% share, for clinical decision support, patient data integration, and research.
E-commerce & Retail - 25%, enabling personalized recommendations and product discovery.
BFSI - 15%, for fraud detection, risk analytics, and regulatory compliance.
Government - 10%, for public data management and smart city initiatives.
Media & Entertainment - 10%, for content recommendation and semantic indexing.
Others - 20%, covering manufacturing, energy, and logistics.

By Region

North America - 35% Share
Market growth driven by early adoption of AI/ML, cloud platforms, and enterprise digital transformation.

Europe - 25% Share
Adoption fueled by industrial knowledge graphs, semantic search applications, and AI integration.

Asia Pacific - 25% Share
Emerging market due to increasing digitalization, e-commerce growth, and AI investments.

Latin America - 7% Share
Opportunities in BFSI, government, and retail sectors.

Middle East & Africa - 8% Share
Growing adoption for knowledge management and AI-based analytics, especially in government and energy sectors.

FAQ

What is the current size of the Knowledge Graph Market?

A: In 2022, the Knowledge Graph Market was valued at US$ 0.7 billion, reflecting its strong industry presence.

Q2: How large is the Knowledge Graph Market expected to be by 2030?

A: By 2030, industry forecasts suggest the Knowledge Graph Market will grow to around US$ 3.6 billion , demonstrating significant expansion.

Q3: What is the growth rate of the Knowledge Graph Market?

A: The market is projected to expand at a compound annual growth rate (CAGR) of 22.1% during the forecast period from 2024 to 2031.

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