At a time when every enterprise looks to leverage generative artificial intelligence, data sites are turning their attention to graph databases and knowledge graphs. The global graph database market ...

The difference is that, in Diffbot's case, the knowledge graph is only partially curated by humans, and is automatically populated by crawling the web. ZDNet talked to Mike Tung, Diffbot's CEO and ...

Graph databases use graph structures for semantic queries, providing a more flexible and efficient way to manage relationships between data.

The Knowledge Graph is powered by both private and public databases, including Wikipedia, Freebase, and the CIA’s World Factbook, that feed into the graph’s current storehouse of information ...

Knowledge Graphs shine in this complex environment by providing a structured representation of relationships between entities, such as policies, claims, and customers.

They saw a difference between search queries and orders but recognized that ... a typical relational database. ... and connect those entities and their relationships into the knowledge graph.

The Bulgarian graph database startup Graphwise today announced a major upgrade to its flagship GraphDB tool, adding new features aimed at boosting enterprise knowledge management and creating a more ...

An essential component for building more trustworthy AI lies in creating a more solid data foundation on top of graph databases, knowledge graphs, and vector databases. Each element plays a ...

In contrast, graph databases are designed to handle complex, interconnected questions more efficiently. They can traverse the data and relationships between customers, purchase history, location ...