Graph databases work best when the data you’re working with is highly connected and should be represented by how it links or refers to other data, typically by way of many-to-many relationships.

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.

A new generation of graph databases has taken hold, and a generation of query languages has arrived alongside them. The assorted graph database query languages include the likes of Gremlin, Cypher ...

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

Fluree touts itself as the Web3 Data Platform -- a semantic graph database that guarantees data integrity, facilitates secure data sharing, and powers connected data insights, all in one pluggable ...

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.

Neo4j has announced the general availability of the next generation of its namesake graph database for both community and enterprise users. Neo4j 5 widens the performance lead of native graphs over ...

Knowledge graphs are on the rise at enterprises that seek more effective ways to connect the dots between the data world and the business world. At Data Summit Connect, a free 3-day series of ...