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 ...

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 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 ...

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 ...

Understanding the relationships in graph database theory allows us to work with the new 'shape' of data itself. Businesspeople like graphs. C-suite executives are fond of pie charts, Venn diagrams, ...

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 ...

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now The graph database stands as one of the ...

Graph database startup TigerGraph Inc. today announced a major update to its flagship cloud platform with the Savanna release, bringing with it six times faster network deployments and dozens of other ...

The problem: The app must store a collection of people and who they know. Sometimes it must find out everyone who knows someone who knows Bob. Sometimes it must look further for everyone who is three ...