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

Extending the success of NoSQL databases and big data solutions, architects are now realizing that a new type of approach to working with data, be it a graph database or a graphing engine, can help ...

In a graph database, every element contains a direct pointer to its adjacent element and no index lookups are necessary. Before looking into a graph database provider, make sure your intended use ...

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.

Emil Eifrem overviews the trends leading to NOSQL, and four emerging NOSQL solutions. He also explains the internals of a graph database and an example of using Neo4j – a graph DB - in production.

Instead, there are four popular types of NoSQL database offerings: document stores, column stores, key/value pairs, and graph databases. A document store manages and stores data at the document level.

The evolving landscape of NoSQL databases and NoSQL database management systems (NoSQL DBMS) has everything to do with Big Data analytics.

Like other NoSQL databases, a graph database is schema-less. Thus, in terms of performance and flexibility, graph databases hew closer to document databases or key-value stores than they do ...

"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 ...

NoSQL and NewSQL databases are popular solutions in the data management space. At VoltDB, we’re sometimes asked to clarify the difference between the two approaches. Here’s what you need to know if ...