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 querying of data housed in massive data lakes and data warehouses has been part of the big data and analytics scene for many years, but it hasn’t always been a particularly easy process.

For a long time, companies have been using relational databases (DB) to manage data. However, with the increasing use of large AI models, integration with graph databases is now required. This process ...

TigerGraph Inc. aims to nudge its graph database closer to the mainstream market with enhancements announced today. The new features include better integration with popular relational and NoSQL ...

eWEEK content and product recommendations are editorially independent. We may make money when you click on links to our partners. Learn More. Just about every enterprise in the world makes use of a ...

Graph databases, which explicitly express the connections between nodes, are more efficient at the analysis of networks (computer, human, geographic, or otherwise) than relational databases. That ...

Graph database provider TigerGraph Inc. today announced version 3.0 of its namesake engine, saying it incorporates significant ease-of-use enhancements. Graph databases are a type of NoSQL database ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Soroosh Khodami discusses why we aren't ready ...

Graph databases such as Neo4j, TigerGraph, Amazon Neptune, the graph portion of Azure Cosmos DB, and AnzoGraph, the subject of this review, offer a natural representation of data that is primarily ...

The Internet of Things is creating serious new security risks. We examine the possibilities and the dangers. Read now Fifty years ago, relational databases were neither ubiquitous nor standardized.