Graph databases have always been useful to help find connections across a vast data set, and it turns out that capability is quite handy in artificial intelligence and machine learning too. Today, ...

Graph databases offer a more efficient way to model relationships and networks than relational (SQL) databases or other kinds of NoSQL databases (document, wide column, and so on). Lately many ...

Victor Lee is director of product management at TigerGraph. Graph databases excel at answering complex questions about relationships in large data sets. But they hit a wall—in terms of both ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Graph database vendor Neo4j announced today new capabilities for vector ...

Graph databases are the fastest growing category in all of data management, according to DB-Engines.com, a database consultancy. Since seeing early adoption by companies including Twitter, Facebook ...

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, ...

Douglas Adams once wrote of a Holistic Detective Agency. The central character in this story, Dirk Gently, was able to solve cases with his understanding of the fundamental interconnectedness of ...