AI and generative technologies have increased demand for databases that can process complex, interconnected workloads. Graph databases and knowledge graphs supply visual, semantic representations that support inference across structured and unstructured data. Graph databases now represent the fastest-growing segment of the $137 billion annual database market, with five-year compound annual growth rates exceeding 24–26%, while the broader DBMS market grows more slowly. Semantic understanding and reasoning requirements for modern AI reveal limitations in flat relational databases. Multiple dedicated graph-database vendors compete to provide backends optimized for AI systems.
More recently, there has been a boom in the use of artificial intelligence (AI), both in backend systems and through the rise of generative technologies, creating an insatiable demand for databases that can handle and process super-sophisticated workloads. This demand has led to the upsurge of graph databases and knowledge graphs, which are visual databases that can help users manage the requirements of AI.
Graph databases have been on the rise for several years and now comprise the fastest-growing category within the $137bn annual database market. Again, thank AI -- graph databases are seen as the most optimal data backend for AI systems. Spending on these technologies will have a five-year compounded annual growth rate of more than 26%, according to published by tech analyst Gartner at the end of 2024. The overall database management system market will grow 16% annually.
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