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, 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 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 ...

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 ...

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 ...

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 ...

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 ...

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 ...