Key-value, document-oriented, column family, graph, relational… Today we seem to have as many kinds of databases as there are kinds of data. While this may make choosing a database harder, it ...

Graph databases have moved from a topic of academic study into the mainstream of information technology in the last few years. Now CIOs are confronted with the need to better understand: What ...

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 are the fastest-growing category in all of data management. Here's how to pick one.

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 ...

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.

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

InfoQ spoke with co-authors of "Graph Databases" book Ian Robinson and Jim Webber about the book, role of Graph Databases in the NoSQL database space, and what’s coming up in the Graph Databases.

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 data science is when you want to answer questions, not just with your data, but with the connections between your data points — that’s the 30-second explanation, according to Alicia Frame.