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 ...

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.

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.

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 ...

A next-generation graph-relational database (DB) system has been developed in South Korea. If this system is applied in industrial settings, artificial intelligence (AI) will be able to perform ...

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, ...