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.

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

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

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.

DZD, the German Federal Diabetes Research Centre, is using a Neo4j graph database to link up Covid-19 scientific research and scientists.

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 ...