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, ...

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 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 ...

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.

Anyone who's ever tried to build distributed applications (dApps) on the (Ethereum) blockchain would concur: Although blockchains are conceptually quite close to databases, querying databases feels ...

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 ...

Every decade seems to have its database. During the 1990s, the relational database became the principal data environment, its ease of use and tabular arrangement making it a natural for the growing ...