Victor Lee is director of product management at TigerGraph. Graph databases excel at answering complex questions about relationships in large data sets. But they hit a wall—in terms of both ...

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 addition of vectors provides context to the graph database for enhanced search and supports generative AI and large language models.

To better explain how graph databases work, I will use IBM Graph, a technology that I helped to build and am excited to teach new users about. Let’s dive in.

Real-time database vendor Aerospike is expanding its multi-model capabilities with the launch of the Aerospike Graph database. Aerospike got its start back in 2009, providing a NoSQL database that ...

One technology experiencing a kind of renaissance is the graph database, which has existed for years but is finding new relevance in current cybersecurity contexts.

Neo4j, the premiere graph database development platform, announced the release of version 4.0 today, which features unlimited scaling among other updates.

Graph database company Neo Technology gets $36m funding boost Company says investment will help "further propel graph technology into the mainstream".

Facebook reaches Social Graph database benchmark: Facebook engineers discuss the development processes behind LinkBench, and how it’s being used at the world's largest social network today.

The graph database is experiencing a surge in popularity, thanks to all of the above. This type of database, which uses graph structures for semantic queries with nodes, edges and properties to ...