Knowledge Graph Market worth $2.4 billion by 2028 - Exclusive Report by MarketsandMarkets™

CHICAGO, Oct. 31, 2023 /PRNewswire/ -- The growing significance of structured data and the growing use of knowledge graphs across many industries will determine the direction of the Knowledge Graph Market in the future. Knowledge graphs will continue to be an important and crucial component of data strategies used by organisations as they work to get valuable insights from their data and realise its full potential.

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, according to MarketsandMarkets. As data ecosystems become more complex, organizations are seeking advanced tools and technologies to manage and derive value from diverse and interconnected data sources. Knowledge graphs provide a comprehensive view of complex data relationships, helping organizations gain insights and derive actionable intelligence from their data ecosystems.

Browse in-depth TOC on "Knowledge Graph Market"

300 - Tables
50 - Figures
350 - Pages

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Scope of the Report

Based on application, the semantic search segment holds the largest market size during the forecast period

Semantic search application is the driving force behind improved search functions and user experiences in the ever-changing Knowledge Graph Market. It provides previously unheard-of levels of search accuracy by understanding the complex subtleties of user queries, making it easy for users to locate extremely relevant and contextual information. They enable users to effortlessly explore interconnected content by supporting natural language inputs and understanding sophisticated queries, creating a more intuitive and user-friendly search experience.

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Based on application, the recommendation systems segment is expected to grow with the highest CAGR during the forecast period

The Knowledge Graph Market is changing as a result of the synergy between recommendation systems and knowledge graphs. Personalized content recommendations, which make use of past data and user preferences, are now considered the standard for user engagement. Recommendation systems have also improved search functionality through integration, making it possible to explore relevant topics and resources more thoroughly and effectively. This has completely changed the way users approach acquiring knowledge, especially when combined with the facilitation of contextualized training and learning. Predictive analytics and trend forecasting, in particular, have made it possible for companies to plan ahead and make well-informed decisions that meet changing market demands. Furthermore, recommendation algorithms provide a widespread knowledge of intricate ideas through cross-domain information integration, which in turn promotes multidisciplinary cooperation in the Knowledge Graph Market.

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

The Knowledge Graph Market in Asia Pacific is highly competitive, as the China, India and Japan have a strong focus on Research and Development (R&D) and innovation. The Asia Pacific digital economy is expanding and experiencing growing regional demand. The technology industry, including mobile, social networking, cloud, and IoT, in the region, is rapidly developing and disrupting. As a manufacturing hub, Asia Pacific should widely adopt knowledge graph solutions and services to remain cost-efficient and export high-quality items to other countries. Companies operating in APAC continue to focus on improving customer services to drive market competitiveness and revenue growth. APAC countries have one of the strongest chances of making rapid advancements in the consumer market. The major industry verticals that are adopting knowledge graph technologies include financial services, healthcare, retail, and manufacturing. Overall, the Asia Pacific Knowledge Graph Market is expected to continue to grow rapidly in the coming years, as organizations in the region increasingly realize the benefits of these technologies.

Top Key Companies in Knowledge Graph Market:

The Knowledge Graph Market comprises major providers, such 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). To increase their market share in the knowledge graph industry, these competitors have used a variety of growth methods, including partnerships, agreements, collaborations, new product releases, product enhancements, and acquisitions.

Recent Developments

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

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Knowledge Graph Market Advantages:

• Knowledge graphs facilitate access to and analysis of information kept in different silos by integrating data from a variety of sources, formats, and disciplines. This allows for a more thorough analysis of the data.
• Knowledge graphs give data a semantic overlay that enables systems to comprehend the context and meaning of information. Applications for machine learning, natural language processing, and more sophisticated search are made possible by this.
• It is now simpler to extract pertinent data from huge, complicated datasets because to knowledge graphs' robust querying capabilities, which facilitate intricate, graph-based searches.
• Systems can better understand data in context with the use of knowledge graphs, which encapsulate the relationships and context between items. Decision assistance, recommendation systems, and personalization can all benefit from this.
• Knowledge graphs offer an integrated perspective on data, enabling academic institutions to derive insights spanning many fields and specialisations, hence stimulating creativity and interdisciplinary teamwork.
• Existing data can be improved and made more comprehensively analyzeable by adding more context and metadata to it through the use of knowledge graphs.
• Knowledge graphs help link articles, webpages, and documents to related concepts and entities in the digital content domain, which enhances content discoverability and recommendation systems.
• Building recommendation engines—which may offer people individualised content, goods, or services based on their interests and behavior—requires the use of knowledge graphs.

Report Objectives

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

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