Peter Neubauer introduces Graph databases and how they compare to RDBMS' and where they stand in the NOSQL-movement, followed by examples of using a graph database in Java with Neo4j.

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.

But with over 100 different NoSQL options to choose from, separated into unfamiliar categories like "document" and "wide column" and "key-value" and "graph," NoSQL's diversity may be its own worst ...

At the high end of the complexity spectrum for NoSQL database lies the graph database, which are highly specialized data stores used for storing linked data. Instead of storing data in rows/columns or ...

The NoSQL taxonomy supports key-value stores, document store, BigTable, and graph databases. MongoDB, for example, uses a document model, which can be thought of as a row in a RDBMS.

Standard, non-graph NoSQL databases — whether key-value, document-oriented, or column-oriented — typically store sets of disconnected values, documents, or columns.

Around the same time as scale-out NoSQL, graph databases emerged. Many things are not “relational” per se, or not based on set theory and relational algebra, but instead on parent-child or ...

Reltio’s first insight is that graphs are most powerful when they reveal new relationships that spring from a combined, curated set of data. As it happens, a body of practices for combining and ...

InfiniteGraph is the latest to throw an offering into the pot, launching a new tool for NoSQL quadrants of databases. It’s an enabling technology really.