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 ...

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.

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, ...

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 ...

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.

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Cory Benfield discusses the evolution of ...

As enterprises continue to navigate the complexities of digital transformation, connected data is becoming an increasingly common necessity. Connected data is when data assets are linked together to ...

Graph databases, such as Neo4j, Apache Spark GraphX, DataStax Enterprise Graph, IBM Graph, JanusGraph, TigerGraph, AnzoGraph, the graph portion of Azure Cosmos DB, and the subject of this review, ...

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 been a ...