Graph databases work best when the data you’re working with is highly connected and should be represented by how it links or refers to other data, typically by way of many-to-many relationships.

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 ...

You can think of a graph database as a set of interconnected circles (nodes) and each node represents a person, a product, a place or ‘thing’ that we want to build into our data universe.

Amazon’s Neptune is a distributed graph database that’s optimized for very large datasets and fast response times. It works with two popular query languages (TinkerPop and SparQL).

AWS makes Neptune, its graph database service, serverless Kyle Wiggers 9:13 AM PDT · October 27, 2022 ...

In a complete graph (left) every node is connected to every other. For other well studied graphs, the Paley graph in the center and the Latin square graph on the right, that is not true.

AnzoGraph DB: Driving AI and Machine Insights with Knowledge Graphs in a Connected World Knowledge Graphs are quickly being adopted because they have the advantages of linking and analyzing vast ...

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 ...

Today, Neo4j, the makers of the open source and commercial graph database platform, announced the release of Neo4j 3.5, which has a number of new features aimed specifically at AI and machine ...