Key-value, document-oriented, column family, graph, relational… Today we seem to have as many kinds of databases as there are kinds of data. While this may make choosing a database harder, it ...

Graph databases have matured into mainstream information technology. They are no longer esoteric software that’s just emerging from the lab of a startup no one has ever heard of.

Graph databases are the fastest-growing category in all of data management. Here's how to pick one.

A semantic graph database technology vendor is supporting a key specification designed to validate graph-based data against a set of conditions that specify the “shape” of data. The goal is a more ...

SQL Server is trusted by many customers for enterprise-grade, mission-critical workloads that store and process large volumes of data. Technologies like in-memory OLTP and columnstore have also helped ...

AnzoGraph is a fast, horizontally scalable, OLAP graph database that brings a wealth of analytics capabilities to large graphs ...

Several graph databases rely on a SQL engine and use a table to store the graph data. Others store data in a key-value store or a document-oriented database, making them fundamentally NoSQL.

Debate and discussion around data management, analytics, BI and information governance. This is a guest blogpost by Neo4j co-founder and CEO Emil Eifrem, who explains why his sector needs its own ...