A graph database is a dynamic database management system uniquely structured to manage complex and interconnected data. Unlike traditional databases organized in rows and columns, graph databases ...

Traditional relational databases are ill-suited for handling the complex, interconnected data of identity management graphs. Instead, graph databases like Neo4j or Amazon Neptune are used.

University of Virginia School of Engineering and Applied Science professor Nikolaos Sidiropoulos has introduced a breakthrough in graph mining with the development of a new computational algorithm.

Franz’s AllegroGraph 7.1 Accelerates Complex Reasoning Across Massive, Distributed Knowledge Graphs and Data Fabrics Distributed FedShard Queries Improved 10X. New SPARQL*, RDF* and SHACL ...

Their method is especially powerful because this complex graph structure does not need to be defined in advance -- the model can learn the graph on its own, in an unsupervised manner.

As organizations undergo digital transformation to analyze and query large amounts of data at high speeds, they are increasingly leveraging graph databases to illuminate information about connections.

Graphs, visual representations outlining the relationships between different entities, concepts or variables, can be very ...

It is a very complex graph theory problem. And the big challenge here for me and it is very different than my previous companies is not how do I handle a billion queries per second, ...

Flow graphs represent computational tasks as nodes and the communication between them as edges. By specifying a dependency graph, the developer expresses all the inter-dependencies between executing ...