Knowledge Graph Market Size was estimated at 0.76 (USD Billion) in 2022. The Knowledge Graph Market Industry is expected to grow from 0.90 (USD Billion) in 2023 to 5.14 (USD Billion) by 2032. The Knowledge Graph Market CAGR (growth rate) is expected to be around 18.6% during the forecast period (2024 - 2032).
Key market drivers for knowledge graphs include the increasing demand for personalized and contextualized information, the growth of artificial intelligence (AI) and machine learning (ML), and the need for organizations to manage and make sense of vast amounts of data.
Opportunities in the knowledge graph market include the development of new applications and services that leverage knowledge graphs, the expansion of knowledge graphs into new domains and industries, and the integration of knowledge graphs with other technologies such as AI and ML.
Recent trends in the knowledge graph market include the adoption of knowledge graphs by major technology companies, the development of new knowledge graph technologies and standards, and the increasing use of knowledge graphs in enterprise applications.
Source: Primary Research, Secondary Research, MRFR Database and Analyst Review
Increased Demand for Personalized Information Retrieval
In today's digital age, users expect personalized and relevant information at their fingertips. Knowledge graphs play a crucial role in meeting this demand by providing a structured and interconnected representation of entities and their relationships. This enables search engines and other applications to understand the context of user queries and deliver highly relevant results. The growing adoption of knowledge graphs in various industries, including e-commerce, healthcare, and finance, is a testament to their ability to enhance information retrieval and improve user experience.
As the demand for personalized information continues to rise, the Knowledge Graph Market Industry is expected to witness significant growth in the coming years.
Advancements in Natural Language Processing (NLP)
Natural language processing (NLP) is a field of artificial intelligence that enables computers to understand and generate human language. Advancements in NLP have significantly contributed to the growth of the Knowledge Graph Market Industry. NLP techniques allow knowledge graphs to extract meaningful insights from unstructured text data, such as news articles, social media posts, and scientific literature. By leveraging NLP, knowledge graphs can automatically populate and update themselves, ensuring that they remain accurate and up-to-date.
The integration of NLP with knowledge graphs has opened up new possibilities for applications in various domains, including sentiment analysis, machine translation, and question-answering.
Rising Adoption of Knowledge Graphs in Enterprise Applications
Enterprises across various industries are increasingly recognizing the value of knowledge graphs for improving decision-making and operational efficiency. Knowledge graphs provide a centralized and structured repository of information that can be easily accessed and analyzed by various applications. This enables enterprises to gain a comprehensive understanding of their customers, products, and operations. By leveraging knowledge graphs, enterprises can optimize supply chains, enhance customer service, and identify new business opportunities.
The growing adoption of knowledge graphs in enterprise applications is a key driver of growth for the Knowledge Graph Market Industry.
The Knowledge Graph Market is segmented by Deployment Model into Cloud-based and On-premises. Cloud-based deployment is expected to hold a significant market share in the coming years due to its scalability, cost-effectiveness, and ease of deployment. Major players in the Knowledge Graph Market are increasingly focusing on offering Cloud-based deployment, which provides several benefits such as flexibility, scalability, and reduced infrastructure costs. It eliminates the need for organizations to invest in hardware and software infrastructure and IT staff to maintain the system.
With Cloud-based deployment, organizations can access the latest features and updates without investing in costly upgrades. On the other hand, on-premises deployment provides organizations with greater control over their data and security. This deployment model is suitable for organizations with sensitive data or those that require compliance with specific regulatory requirements. However, on-premises deployment can be more expensive and complex to implement and maintain compared to Cloud-based deployment. The choice between Cloud-based and on-premises deployment depends on various factors, including the organization's size, industry, budget, and specific requirements.
Overall, the Knowledge Graph Market is expected to benefit from the growing adoption of Cloud-based deployment, which is expected to drive market growth in the coming years.
Source: Primary Research, Secondary Research, MRFR Database and Analyst Review
The Knowledge Graph Market segmentation by Industry Vertical is expected to witness significant growth in the coming years. In 2023, the Healthcare segment held the largest market share, accounting for around 25% of the Knowledge Graph Market revenue. The Financial Services segment is expected to grow at a rapid pace in the coming years, driven by the increasing demand for knowledge graphs to improve customer service and risk management. The Retail segment is also expected to witness significant growth, as knowledge graphs can be used to personalize the shopping experience and provide customers with relevant recommendations.
The Manufacturing segment is expected to grow steadily, as knowledge graphs can be used to improve supply chain management and optimize production processes. The IT Telecom segment is also expected to witness growth, as knowledge graphs can be used to improve network management and customer support.
The Knowledge Graph Market is segmented by data source into structured, unstructured, and semi-structured data. Structured data is data that is organized in a way that makes it easy for computers to read and process. This type of data is typically stored in databases and spreadsheets. Examples of structured data include customer names, addresses, and order histories. Unstructured data is data that is not organized in a way that makes it easy for computers to read and process. This type of data is typically stored in text files, emails, and social media posts.
Examples of unstructured data include product reviews, customer feedback, and news articles. Semi-structured data is data that is partially organized, but not as organized as structured data. This type of data is typically stored in XML files and JSON files. Examples of semi-structured data include product catalogs, financial statements, and medical records. The structured data segment is expected to account for the largest share of the Knowledge Graph Market in 2023. This is because structured data is easier for computers to read and process than unstructured data.
As a result, structured data is more likely to be used in applications that require real-time decision-making. The unstructured data segment is expected to grow at the fastest rate over the next five years. This is because unstructured data is becoming increasingly important in a variety of applications, such as natural language processing and machine learning. The semi-structured data segment is expected to account for a small share of the Knowledge Graph Market in 2023. However, this segment is expected to grow at a steady rate over the next five years.
The Knowledge Graph Market is segmented into North America, Europe, Asia-Pacific, South America, and the Middle East and Africa. North America held the largest market share in 2023 and is expected to maintain its dominance throughout the forecast period. The region's large number of technology companies and research institutions, as well as its high adoption of AI and machine learning, are driving the growth of the Knowledge Graph Market in North America. Europe is the second-largest market for Knowledge Graphs and is expected to grow steadily over the forecast period.
The region's strong focus on data privacy and security, as well as its growing number of startups in the AI and machine learning space, are contributing to the growth of the Knowledge Graph Market in Europe. APAC is the fastest-growing region for Knowledge Graphs and is expected to witness significant growth over the forecast period. The region's rapidly growing economy, as well as its large population of internet users, are driving the growth of the Knowledge Graph Market in APAC. South America, the Middle East, and Africa are expected to grow at a moderate pace over the forecast period.
These regions have a growing number of technology companies and research institutions, as well as a growing number of internet users, which are driving the growth of the Knowledge Graph Market in these regions.
Source: Primary Research, Secondary Research, MRFR Database and Analyst Review
Major players in Knowledge Graph Market industry are constantly striving to gain a competitive edge by developing innovative Knowledge Graph Market solutions and expanding their reach. Leading Knowledge Graph Market players are investing heavily in research and development to stay ahead of the curve and meet the evolving needs of their customers. The Knowledge Graph Market industry is witnessing a trend towards consolidation, with larger players acquiring smaller companies to strengthen their market position and expand their product offerings.
One of the key strategies employed by major players in the Knowledge Graph Market is strategic partnerships and collaborations. Partnerships enable companies to combine their expertise and resources, share knowledge, and gain access to new markets. For instance, Google has partnered with a number of leading universities and research institutions to advance the development and application of Knowledge Graph technology. Another common strategy is product differentiation. Companies are focusing on developing unique and innovative Knowledge Graph solutions that cater to specific industry needs and address specific customer pain points.
Furthermore, market participants are actively involved in international expansion to capitalize on growth opportunities in emerging markets. They are adapting their Knowledge Graph offerings to meet local market requirements and cultural nuances. This international expansion is expected to drive the growth of the Knowledge Graph Market in the coming years.
SAP
FactSet
Thomson Reuters
Wolfram Research
Moody's
S Global
Oracle
Fitch Solutions
Bloomberg
LexisNexis
IBM
Wolters Kluwer
Microsoft
Amazon
Relx
The Knowledge Graph Market is anticipated to reach a valuation of USD 173.7 billion by 2032, expanding at a CAGR of 30.93% from 2024 to 2032. This growth is driven by the increasing adoption of AI and machine learning technologies, the growing need for efficient data management and analysis, and the rising demand for personalized and contextualized information. Recent developments in the market include the launch of new Knowledge Graph platforms by major technology companies, such as Google's Knowledge Graph Search API and Amazon's Knowledge Graph. Additionally, there have been several acquisitions and partnerships in the market, such as Google's acquisition of DeepMind and Microsoft's partnership with LinkedIn to enhance their Knowledge Graph capabilities.
Cloud-based
On-premises
Healthcare
Financial Services
Retail
Manufacturing
IT Telecom
Structured
Unstructured
Semi-structured
North America
Europe
South America
Asia Pacific
Middle East and Africa
| Report Attribute/Metric | Details |
| Market Size 2022 | 0.76 (USD Billion) |
| Market Size 2023 | 0.90 (USD Billion) |
| Market Size 2032 | 5.14 (USD Billion) |
| Compound Annual Growth Rate (CAGR) | 18.6% (2024 - 2032) |
| Report Coverage | Revenue Forecast, Competitive Landscape, Growth Factors, and Trends |
| Base Year | 2023 |
| Market Forecast Period | 2024 - 2032 |
| Historical Data | 2019 - 2023 |
| Market Forecast Units | USD Billion |
| Key Companies Profiled | SAP, FactSet, Thomson Reuters, Wolfram Research, Moody's, S Global, Oracle, Fitch Solutions, Bloomberg, LexisNexis, IBM, Wolters Kluwer, Google, Microsoft, Amazon, Relx |
| Segments Covered | Deployment Model, Industry Vertical, Data Source, Regional |
| Key Market Opportunities | Enterprise Knowledge ManagementEcommerce and Search PersonalizationFraud Detection and Risk ManagementHealthcare Information IntegrationRealtime Insights for DecisionMaking |
| Key Market Dynamics | Growing adoption of AI and machine learning Enhanced knowledge discovery and automated reasoningRising demand for personalized experiences Tailored content and recommendations based on individual user preferencesEmergence of semantic search and natural language processing Improved search accuracy and efficiency.Increased focus on data privacy and security, Ensuring the protection of sensitive information.Growing investment in knowledge graph development Expanding capabilities and applications |
| Countries Covered | North America, Europe, APAC, South America, MEA |
Frequently Asked Questions (FAQ) :
The Knowledge Graph Market is expected to reach a valuation of USD 0.90 billion in 2023.
The Knowledge Graph Market is projected to grow at a CAGR of 18.6% from 2024 to 2032
The growth of the Knowledge Graph Market is primarily driven by the increasing adoption of AI and machine learning technologies, the growing need for data integration and interoperability, and the rising demand for personalized and contextualized information.
North America is expected to hold the largest market share in the Knowledge Graph Market due to the early adoption of AI and machine learning technologies, the presence of major technology companies, and the increasing demand for data-driven insights.
Key competitors in the Knowledge Graph Market include Google, Microsoft, Amazon, IBM, and Oracle.
Major applications of Knowledge Graphs include search engine optimization (SEO), natural language processing (NLP), question answering, and data integration.
Challenges faced by the Knowledge Graph Market include data privacy and security concerns, the lack of standardized data formats, and the need for skilled professionals.
Expected trends in the Knowledge Graph Market include the increasing adoption of cloud-based Knowledge Graphs, the integration of Knowledge Graphs with other emerging technologies such as blockchain and the Internet of Things (IoT), and the growing demand for real-time data integration.
The Knowledge Graph Market is expected to reach a valuation of USD 173.7 billion by 2032.
Key opportunities for growth in the Knowledge Graph Market include the increasing adoption of AI and machine learning technologies, the growing demand for data integration and interoperability, and the rising demand for personalized and contextualized information.
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