Key-value, document-oriented, column family, graph, relational… Today we seem to have as many kinds of databases as there are kinds of data. While this may make choosing a database harder, it ...

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

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

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 ...

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.

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. Paired with complementary AI technologies such as ...

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

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.