A sui generis, multi-model open source database, designed from the ground up to be distributed. ArangoDB keeps up with the times and uses graph, and machine learning, as the entry points for its ...

To stay visible in AI search, your content must be machine-readable. Schema markup and knowledge graphs help you define what ...

Enter knowledge-graph-powered data intelligence platforms with metadata management capabilities. Google popularized the term "knowledge graph" in this 2012 blog post.

When given access to multiple enterprise data stores, graph databases can offer entirely new insights and capabilities. Yu Xu is CEO of TigerGraph.

Connecting And Leveraging Data Knowledge graph technology is transforming the way that organizations manage and make sense of data: A Unified View: By integrating data from multiple sources ...

A knowledge graph is like that car’s navigation system, providing context, meaning, and direction on top of those connections.” The bottom line is that “graph databases are a type of NoSQL database ...

Graph analytics databases have been described as embodying the next generation of data storage connected with AI, and that's what innovation is all about: a new-and-improved version of how ...

Also bringing graphs to the modern data management stack are graph specialists such as Cambridge Semantics, Franz, Neo4j, TigerGraph and others. Multimodel databases have come to support a Swiss ...

For most fields, graphs are the most common form of visual presentation for data. Graphs exist in numerous shapes and formats, but as a rule, should only be used to present trends or relationships ...