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.

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.

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

Graph database company Neo4j wants to move beyond providing only its graph database, and is working on what it calls a 'graph platform' to help companies make the most of their data. ZDNet ...

Graph databases excel for apps that explore many-to-many relationships, such as recommendation systems. Let’s look at an example ...

Graph databases are powerful new tools for managing and analyzing heterogeneous data across the enterprise. Most importantly, organizations are beginning tounderstand the specific use cases that graph ...

Still using an RDBMS for friend-of-a-friend queries? Big mistake. Enlist a graph database using Neo4j instead.

Real-time database vendor Aerospike is expanding its multi-model capabilities with the launch of the Aerospike Graph database. Aerospike got its start back in 2009, providing a NoSQL database that ...

"Graph Databases" book covers the Graph based NoSQL database technology and different options available for storing "Connected Data" in the real world applications. InfoQ spoke with co-authors Ian ...

Emerging graph database benchmarks are already helping to overcome performance, scalability and reliability issues.