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

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

MarketsandMarkets forecasts that the knowledge graph market size is projected to grow from USD 0.9 billion in 2023 to USD 2.4 billion by 2028, at a CAGR of 21.8% during the forecast period. Organizations increasingly focus on knowledge discovery and management to improve decision-making processes and gain actionable insights. Knowledge graphs help organize complex information and extract valuable knowledge from structured and unstructured data, contributing to more informed decision-making.

“By vertical, the IT & ITeS segment is expected to grow with the highest CAGR during the forecast period.”

The market for knowledge graphs in the IT & ITeS sector has expanded and is expected to change significantly in the coming years, demonstrating the market's critical role in data management and knowledge representation. Knowledge graphs are essential for integrating diverse data and facilitating well-informed decision-making in various industries, including e-commerce, healthcare, finance, and others. These graphs have further strengthened search engines and recommendation systems, giving users more accurate and customized results. Thanks to integration with AI systems and semantic technologies, they can now comprehend complicated relationships and situations much better.

“By data source, the unstructured data segment is expected to hold the largest market size during the forecast period.”

Research in data enrichment, contextual understanding, and semantic analysis has advanced significantly as a result of the knowledge graph market's increasing focus on unstructured data sources. Through the application of advanced natural language processing algorithms, enterprises can obtain significant insights from a variety of unstructured data sources, such as textual content, social media feeds, and customer reviews. Because of the abundance of rich data, the knowledge graph can provide a more thorough and integrated understanding of different disciplines, leading to more precise insights and customized suggestions.

“Asia Pacific is expected to grow with the highest CAGR during the forecast period.”

The Asia Pacific region has become a hotbed for the rapid adoption of knowledge graphs, owing to its dynamic technological landscape and the increasing complexity of data. With a strong emphasis on data-driven decision-making and a burgeoning need for personalized customer experiences, businesses have turned to knowledge graphs as a solution to manage and analyze intricate datasets from diverse sources. Government initiatives supporting technological advancements have further fueled the growth of the knowledge graph market, facilitating innovation and economic development. As the region continues to invest in cutting-edge technologies, the potential for knowledge graphs to streamline data management and drive insightful decision-making remains a key focal point for businesses and organizations across various sectors.

Breakdown of primaries

The study contains insights from various industry experts, from solution vendors to Tier 1 companies. The break-up of the primaries is as follows:

By Company: Tier 1–20%, Tier 2–25%, and Tier 3–55%

By Designation: C-Level Executives–40%, Director Level–33%, and Others–27%

By Region: North America–32%, Europe–38%, APAC–18%, RoW–12%

The major players in the Knowledge graph market IBM (US), Microsoft (US), AWS (US), Neo4j (US), TigerGraph (US), SAP (Germany), Oracle (US), Stardog (US), Franz Inc (US), Ontotext (Bulgaria), Semantic Web Company (Austria), OpenLink Software (US), MarkLogic (US), Datavid (UK), GraphBase (Australia), Cambridge Semantics (US), CoverSight (US), Eccena Gmbh (Germany), ArangoDB (US), Fluree (US), DiffBot (US), Bitnine (US), Memgraph (England), GraphAware (UK), Onlim (Austria). These players have adopted various growth strategies, such as partnerships, agreements and collaborations, new product launches, product enhancements, and acquisitions to expand their footprint in the knowledge graph market.

Research Coverage

The report segments the global Knowledge graph market by offering into two categories: solutions and services. By model type, the knowledge graph market is divided into four categories: RDF graph, conceptual graph, and semantic graph. By data source, the knowledge graph market is divided into three major categories: structured data, unstructured data, and semi-structured data. By application, the knowledge graph market has been classified into semantic search, question answering, recommendation systems, enterprise knowledge management, and other applications. By type, the knowledge graph market is divided into three categories: context-rich knowledge graphs, external-sensing knowledge graphs, and NLP knowledge graphs. By vertical, the knowledge graph market has been classified into BFSI, retail & e-commerce, manufacturing & automotive, IT and ITES, telecom, media and entertainment, healthcare, government, and other verticals (education, research, and real estate). By region, the market has been segmented into North America, Europe, Asia Pacific, Middle East & Africa, and Latin America.

Key benefits of the report

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

The report provides insights on the following pointers:

Analysis of key drivers (Rapid growth in data volume and complexity, AI and ML to drive market growth, Semantic web and linked data initiatives to boost the market), restraints (Cost of development and maintenance), opportunities (NLP to boost knowledge graph market, increasing adoption in healthcare and life sciences), and challenges (Data quality and integration, Scalability) influencing the growth of the knowledge graph market.

Product Development/Innovation: Detailed insights on upcoming technologies, research and development activities, and new product and service launches in the knowledge graph market.

Market Development: Comprehensive information about lucrative markets – the report analyses the knowledge graph market across varied 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 players IBM (US), Microsoft (US), AWS (US), Neo4j (US), TigerGraph (US), SAP (Germany), Oracle (US), Stardog (US), Franz Inc (US), Ontotext (Bulgaria), Semantic Web Company (Austria), OpenLink Software (US), MarkLogic (US), Datavid (UK), GraphBase (Australia), Cambridge Semantics (US), CoverSight (US), Eccena Gmbh (Germany), ArangoDB (US), Fluree (US), DiffBot (US), Bitnine (US), Memgraph (England), GraphAware (UK), Onlim (Austria).