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.

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 ...

The popular NoSQL database adds graph capabilities to its data platform.

Graph databases store data as nodes and edges (Source: Neo4j) Property graphs have strict schemas, which makes them somewhat an anomaly in the free-floating world of the NoSQL data family. They ...

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

Reltio is a product that combines Master Data Management (MDM) with the power of the Cassandra NoSQL and graph databases to create a new kind of application development platform for data-heavy use ...

Amazon's new graph NoSQL database Neptune can be used to build and run applications that work with highly connected datasets. It also supports read replicas, point-in-time recovery, continuous ...

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.

Like most NoSQL database systems, graph databases are not a general replacement for the relational databases that have been the mainstay of business data storage for the last two decades. Rather, they ...