Graphs in AQL

You can perform graph traversals and path searches on named graphs as well as collection sets with AQL

There are multiple ways to work with graphs in ArangoDB, as well as different ways to query your graphs using AQL.

The two options in managing graphs are to either use

  • named graphs where ArangoDB manages the collections involved in one graph, or
  • graph functions on a combination of document and edge collections.

Named graphs can be defined through the graph-module or via the web interface. The definition contains the name of the graph, and the vertex and edge collections involved. Since the management functions are layered on top of simple sets of document and edge collections, you can also use regular AQL functions to work with them.

Both variants (named graphs and loosely coupled collection sets a.k.a. anonymous graphs) are supported by the AQL language constructs for graph querying. These constructs make full use of optimizations and therefore best performance is to be expected:

  • AQL Traversals to follow edges connected to a start vertex, up to a variable depth. It can be combined with AQL filter conditions.

  • AQL Shortest Path to find one shortest path between two given documents.

  • AQL All Shortest Paths to find all shortest paths between two given documents.

  • AQL k Shortest Paths to find the first k paths in order of length (or weight) between two given documents.

  • AQL k Paths to find all paths between two given documents.

These types of queries are only useful if you use edge collections and/or graphs in your data model.

New to graphs? Take our free graph course for freshers  and get from zero knowledge to advanced query techniques.