What is a Graph Database?
A graph database stores data in a graph, the most generic of data structures, capable of elegantly representing any kind of data in a highly accessible way.
Let’s follow along some graphs, using them to express themselves. We’ll “read” a graph by following arrows around the diagram to form sentences.
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A Graph contains Nodes and Relationships
A Graph –[:RECORDS_DATA_IN]–> Nodes –[:WHICH_HAVE]–> Properties.
The simplest possible graph is a single Node, a record that has named values referred to as Properties. A Node could start with a single Property and grow to a few million, though that can get a little awkward. At some point it makes sense to distribute the data into multiple nodes, organized with explicit Relationships. -
Query a Graph with a Traversal
A Traversal –navigates–> a Graph; it –identifies–> Paths –which order–> Nodes.
A Traversal is how you query a Graph, navigating from starting Nodes to related Nodes according to an algorithm, finding answers to questions like “what music do my friends like that I don’t yet own,” or “if this power supply goes down, what web services are affected?” -
Indexes Look-up Nodes or Relationships
An Index –maps from–> Properties –to either–> Nodes or Relationships. It –is a special–> Traversal.
Often, you want to find a specific Node or Relationship according to a Property it has. This special case of Traversal is so common that it is optimized into an Index look-up, for questions like “find the Account for username master-of-graphs.” -
Why Graphs
Emil Eifrem explains the secret behind websites like Twitter, Yelp and Facebook.Watch the video »
Graph Databases
Jim Webber, Ian Robinson
Exclusive early access to the definitive book on graph databases, published by O"Reilly Media.
What is Neo4j?
Neo4j is a graph database, reliable and fast for managing and querying highly connected data.
The Cypher track
The Cypher track concentrates on the Cypher Graph Query language, making interaction with Neo4j framework independent.
