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.

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 ...

Graph databases like Neo4J and ArrangoDB are mainly designed to store networks or interconnected nodes, but they often also use NoSQL’s simple model for the data stored at these nodes.

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 ...

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 ...

Although a global graph database market estimated at $1.9 Billion in 2021 is expected to grow at 22.5% over the next five years, arguments continue on whether NoSQL graph databases are just ...

NoSQL databases can take a number of forms. They can be cloud services or install on-premises. They can support one or more data models: key-value, document, column, graph, and sometimes even ...

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 ...