Database systems such as MongoDB and MarkLogic store data simply as a collection of documents, making search more efficient and powerful. There are a number of non-relational databases for the Hadoop ...

Imagine a graph database that's not aimed at the growing graph database market, selling to Fortune 500 without sales, and claiming to be the fastest without benchmarks. Dgraph is unique in some ...

A hitherto under the radar graph database that uses blockchain to support data lineage and verification wants to take over the world, starting with the US Department of Defense ...

The addition of vectors provides context to the graph database for enhanced search and supports generative AI and large language models.

TigerGraph Inc. is upgrading its graph database with a hybrid search capability designed to power artificial intelligence applications. The Redwood City, California-based startup debuted the ...

The graph database was originally designed to store networks — that is, the connections between several elements such as people, places they might visit, or the things they might use.

In terms of actual adoption, the fastest growing segment of the database market actually belongs to graph databases that are increasingly being used to drive new classes of applications that require ...

Graph databases, based on mathematics known for three centuries, are starting to yield value for businesses beyond Facebook and Twitter.

Knowledge graphs are a valuable tool that organizations can use to manage the vast amounts of data they collect, store, and analyze. At Data Summit 2022, Joseph Hilger, COO, Enterprise Knowledge LLC ...

Banks, miners and police forces in Australia are among those using graph databases to provide the context and data relationships needed for more accurate and trustworthy AI, moving projects from ...