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

Another thing to be aware of is that some graph databases only offer the graph model, but the underlying implementation is backed by a traditional, relational or other type of NoSQL database.

As graph database adoption accelerates, new data infrastructures will emerge to eliminate many of the scale struggles of graph database models.

A NoSQL database has flexible data requirements, making it a better fit for applications that will evolve over time than an SQL database.

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 ...

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 ...

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 ...

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.

Everywhere you look, there are new NoSQL databases — or “data stores,” if you’re one of those who feel that the word “database” can only be used by proper relational software offering ...

A relational database is no longer the default choice. Mike Loukides charts the rise of the NoSQL movement and explains how to choose the right database for your application.

Today Neo Technology, makers of the NoSQL graph database Neo4j announced that it has raised a $11 million Series B led by Sunstone Capital with participation from previous investors such as ...