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.

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 ...

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

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.

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 ...

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.

If you want to know what’s what in Big Data analytics today, you’ve got to know the basics of NoSQL databases , and how appropriate NoSQL databases facilitate Big Data analytics.

The Global Graph Database Market size is expected to reach $8.1 billion by 2028, rising at a market growth of 22.2% CAGR during the forecast period.A graph database is a single-pu ...

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 ...