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

With the rapid development of artificial intelligence (AI) technology, the graph database market is experiencing unprecedented growth, with an annual growth rate approaching 25%. Graph databases are ...

For a long time, companies have been using relational databases (DB) to manage data. However, with the increasing use of ...

Graph technology is well on its way from a fringe domain to going mainstream. We take a look at the state of the union in graph, featuring Neo4j's latest release and insights as well as data and ...

When DataStax acquired Aurelius, a graph database startup last year, it was clear it wanted to add graph database functionality to its DataStax Enterprise product, and today it achieved that goal ...

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

Infinigraph is a new distributed graph architecture that allows Neo4j’s database to run operational and analytical workloads ...

For a long time, companies have been using relational databases (DB) to manage data. However, with the increasing use of ...

Graph databases facilitate discovery and analysis closely connected facts. This post is one of a series that introduces the fundamentals of NOSQL databases, and their role in Big Data Analytics.

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.