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 ...

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.

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.

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, ...

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 ...

GraphQL seems to be spreading like wildfire, and there's a reason for that. As REST APIs are proliferating, the promise of accessing them all through a single query language and hub, which is what ...

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 development of database technology is one of the defining achievements of the information technology era. It not only has been the key to dramatically improved record-keeping and business process ...