Data-hungry AI applications are fed complex information, and that's where graph databases and knowledge graphs play a crucial role.

The state of graph databases worldwide The State of Graph Databases Worldwide A few days ago, ""=""> a report on the adoption and use case characteristics of graph databases.

Graph databases that use nodes and properties to represent and store data appear to be making significant inroads in the U.S. retail market. For example, graph database specialist Neo Technology of ...

Graph database startup Neo4j raised $320 million at an over $2 billion valuation, highlighting the value of graph databases.

Graph databases are powerful new tools for managing and analyzing heterogeneous data across the enterprise. Most importantly, organizations are beginning tounderstand the specific use cases that graph ...

For example, with LLMs and RAG systems, “using graph databases to map relationships within vast datasets can uncover deeper insights—such as better recommendations or enhanced search results—making ...

A startup named TigerGraph emerged from stealth today with a new native parallel graph database that its founder thinks can shake up the analytics market.

Graph databases are finding favor for their unique ability to represent complex relationships that rapidly navigate between elements in the database to discover correlations.

Graph databases will never replace conventional relational databases, but for harnessing the value of the fundamental interconnectedness of everything, a graph database is well worth considering.

Graph databases power data journalism on the biggest information leak ever.