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

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

Graph database company Neo4j wants to move beyond providing only its graph database, and is working on what it calls a 'graph platform' to help companies make the most of their data. ZDNet ...

A next-generation graph-relational database (DB) system has been developed in South Korea. If this system is applied in ...

Graph databases excel for apps that explore many-to-many relationships, such as recommendation systems. Let’s look at an example Jeff Carpenter is a technical evangelist at DataStax. There has ...

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.

Forrester Research analysts recently reported that graph databases — the fastest growing category in database management systems — will reach more than a quarter of enterprises by 2017.

Graph databases will never replace conventional relational databases, but for harnessing the value of the fundamental interconnectedness of everything, a graph database is well worth considering.

Graph databases are becoming the next big thing in data and analytics technology. According to Gartner, the application of graph processing and graph database management systems will grow at 100% ...

Event host TigerGraph, which makes a graph database that it claims is the only scalable one available for enterprises, has announced the final agenda and speaker lineup for “ Graph + AI World ...