You can think of a graph database as a set of interconnected circles (nodes) and each node represents a person, a product, a place or ‘thing’ that we want to build into our data universe.

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

The graph database is popular with social networks, but there's no reason to limit it to tracking people and their friendships.

Neo4j also trumpeted the value of graphs as vector databases used in generative artificial intelligence. AI training requires ...

Neo4j ®, the leading graph database and analytics platform, today unveiled Infinigraph: a new distributed graph architecture now available in Neo4j's self-managed offering. Infinigraph enables Neo4j's ...

Lyft's "Amundsen" metadata system is an example of how knowledge graphs are spreading throughout companies with grass-roots projects. It's all part of winning hearts and minds, in the view of ...

Knowledge Graphs are quickly being adopted because they have the advantages of linking and analyzing vast amounts of interconnected data. The promise of graph technology has been there for a decade.

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

The big data revolution is generating a mess of unruly data that’s difficult to parse and understand. This is to be expected–explosions don’t generally occur in a nice, orderly fashion, after all. But ...

Amazon is in the middle of its AWS Re:INVENT keynote right now, and the company just announced a brand new database service. Amazon Neptune has been ...