Graph database vs. relational database. In a traditional relational or SQL database, the data is organized into tables. Each table records data in a specific format with a fixed number of columns ...

A graph database is a dynamic database management system uniquely structured to manage complex and interconnected data. Unlike traditional databases organized in rows and columns, graph databases ...

The graph database was originally designed to store networks — that is, the connections between several elements such as people, places they might visit, or the things they might use.

Graph databases have been around in one form or another since the early oughts, ... with other integrated database systems, such as JSON or XML stores, or with search engines.

You can think of a graph database as a set of interconnected circles (nodes) and each node represents a person, a product, a place or ‘thing’ that we want to build into our data universe.

RDF is a graph data model that has been around since 1997. It's a W3C standard, and it's used to power schema.org and Open Graph, among other things. Plus, there's a bunch of RDF-based graph ...

Graph databases are a great tool for helping vendors to improve their tools and for enterprises to assess the veracity of vendor claims using an apples-to-apples comparison.

Aerospike Inc., maker of a highly scalable NoSQL database, today is entering the graph database market with an offering that it claims can outperform and outscale offerings from market leaders ...

The number one graph database, Neo4j, is kicking off its Graph Connect event today and announcing a new version, 3.3. This version brings extended support for querying in Spark, ETL, analytics ...

Some graph database products on the market are really wrappers built on top of a more generic NoSQL data store. This virtual graph strategy has a double penalty when it comes to performance.