(MENAFN- ein presswire) complex data modeling, real-time processing, graph analytics, and cognitive computing are driving the graph database market's growth.
portland, oregon, united states, june 29, 2023/einpresswire / -- the graph database market size was $651 million in 2018 and is anticipated to rise to $3,731 million by 2026, at a cagr of 24.5%.
the rise in the use of graph database software in the healthcare industry, expansion of graph database's application areas, demand for faster response times & accuracy to find new data correlations, and increase in the penetration of connected data to improve marketing performance are the main drivers of the global graph database market's expansion. the market is also being driven by an increase in the use of virtualization for big data analytics and technological developments in graph database technology.
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traditional relational databases struggle with complex relationships and interconnected data. graph databases, on the other hand, excel at capturing and representing relationships between data points. organizations are increasingly adopting graph databases to model and analyze complex networks, such as social networks, recommendation engines, fraud detection systems, and supply chain management. graph databases provide a more efficient and intuitive way to query and traverse relationships, leading to improved insights and decision-making.
with the increasing volume and velocity of data, organizations require real-time data processing capabilities. graph databases offer high-performance querying and traversing of relationships, enabling real-time data analysis. this is particularly crucial in use cases such as fraud detection, real-time recommendations, network analysis, and iot applications. the ability of graph databases to process and analyze real-time data in a connected manner drives their adoption and fuels market growth.
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graph databases provide a foundation for advanced graph analytics and machine learning techniques. by leveraging the graph structure and relationship insights, organizations can apply graph algorithms and machine learning models to uncover hidden patterns, make predictions, and gain deeper insights from their data. the integration of graph databases with graph analytics and machine learning technologies drives the adoption of graph databases as organizations seek to extract value from interconnected data.
the rise of cognitive computing and knowledge graph applications is a significant driver for the graph database market. organizations are increasingly building knowledge graphs, which capture and represent complex relationships between entities, enabling more intelligent and context-aware systems. graph databases serve as the backbone for knowledge graph implementations, facilitating efficient storage, querying, and reasoning over interconnected data. the growing adoption of cognitive computing and knowledge graph applications drives the demand for graph databases.
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some of the key market players profiled in the report include datastax, franz inc., neo4j, inc., oracle corporation, orientdb, mongodb, objectivity inc., stardog union inc., teradata corporation, and microsoft corporation. this study includes graph database market analysis, trends, and future estimations to determine the imminent investment pockets.
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david correa
allied analytics llp
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