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.

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 ...

Graph database query languages are growing, along with graph databases. They let developers ask complex questions and find relationships.

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

Graph databases have always been useful to help find connections across a vast data set, and it turns out that capability is quite handy in artificial ...

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.

But the Microsoft Graph and LinkedIn aren’t Microsoft’s only graphs with APIs: Dynamics 365 has the Common Data Service, a way of describing standard items in a business.

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 ...