Imagine your database of choice blown out of the water by a startup emerging from stealth. TigerGraph may have done just that for graph databases.

A graph is a network of things, called nodes, with their relationships expressed as links, called edges. The nodes in a graph database can be tagged with properties, which are additional information ...

By combining ontology and large language model-driven techniques, engineers can build a knowledge graph that is easily queried and updatable.

Data-hungry AI applications are fed complex information, and that's where graph databases and knowledge graphs play a crucial role.

Graph databases aspire to overcome these problems by adopting a data model in which the relationships between objects or entities are equally as important as the objects themselves. In a graph ...

Graph databases facilitate discovery and analysis closely connected facts. This post is one of a series that introduces the fundamentals of NOSQL databases, and their role in Big Data Analytics.

At Data Summit Connect 2020, Thomas Cook, director of sales, Cambridge Semantics, explained the basics of knowledge graphs and how they leverage natural-language processing to automate the ...

The Neo4j graph database is proving to be popular in the medical community for connecting different entities.

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 ...

Graph databases power data journalism on the biggest information leak ever.