ArangoDB v3.10 reached End of Life (EOL) and is no longer supported.

This documentation is outdated. Please see the most recent stable version.

AQL Query Patterns and Examples

Create test data, count documents, use joins, group attributes, traverse graphs, and other examples

These pages contain some common query patterns with examples. For better understandability the query results are also included directly below each query.

Normally, you would want to run queries on data stored in collections. This section will provide several examples for that.

Some of the following example queries are executed on a collection users with the data provided here below.

Things to consider when running queries on collections

Note that all documents created in any collections will automatically get the following server-generated attributes:

  • _id: A unique id, consisting of collection name and a server-side sequence value
  • _key: The server sequence value
  • _rev: The document’s revision id

Whenever you run queries on the documents in collections, don’t be surprised if these additional attributes are returned as well.

Please also note that with real-world data, you might want to create additional indexes on the data (left out here for brevity). Adding indexes on attributes that are used in FILTER statements may considerably speed up queries. Furthermore, instead of using attributes such as id, from and to, you might want to use the built-in _id, _from and _to attributes. Finally, edge collections provide a nice way of establishing references/links between documents. These features have been left out here for brevity as well.

Example data

Some of the following example queries are executed on a collection users with the following initial data:

[ 
  { "id": 100, "name": "John", "age": 37, "active": true, "gender": "m" },
  { "id": 101, "name": "Fred", "age": 36, "active": true, "gender": "m" },
  { "id": 102, "name": "Jacob", "age": 35, "active": false, "gender": "m" },
  { "id": 103, "name": "Ethan", "age": 34, "active": false, "gender": "m" },
  { "id": 104, "name": "Michael", "age": 33, "active": true, "gender": "m" },
  { "id": 105, "name": "Alexander", "age": 32, "active": true, "gender": "m" },
  { "id": 106, "name": "Daniel", "age": 31, "active": true, "gender": "m" },
  { "id": 107, "name": "Anthony", "age": 30, "active": true, "gender": "m" },
  { "id": 108, "name": "Jim", "age": 29, "active": true, "gender": "m" },
  { "id": 109, "name": "Diego", "age": 28, "active": true, "gender": "m" },
  { "id": 200, "name": "Sophia", "age": 37, "active": true, "gender": "f" },
  { "id": 201, "name": "Emma", "age": 36,  "active": true, "gender": "f" },
  { "id": 202, "name": "Olivia", "age": 35, "active": false, "gender": "f" },
  { "id": 203, "name": "Madison", "age": 34, "active": true, "gender": "x" },
  { "id": 204, "name": "Chloe", "age": 33, "active": true, "gender": "f" },
  { "id": 205, "name": "Eva", "age": 32, "active": false, "gender": "f" },
  { "id": 206, "name": "Abigail", "age": 31, "active": true, "gender": "f" },
  { "id": 207, "name": "Isabella", "age": 30, "active": true, "gender": "f" },
  { "id": 208, "name": "Mary", "age": 29, "active": true, "gender": "f" },
  { "id": 209, "name": "Mariah", "age": 28, "active": true, "gender": "f" }
]

For some of the examples, we’ll also use a collection relations to store relationships between users. The example data for relations are as follows:

[
  { "from": 209, "to": 205, "type": "friend" },
  { "from": 206, "to": 108, "type": "friend" },
  { "from": 202, "to": 204, "type": "friend" },
  { "from": 200, "to": 100, "type": "friend" },
  { "from": 205, "to": 101, "type": "friend" },
  { "from": 209, "to": 203, "type": "friend" },
  { "from": 200, "to": 203, "type": "friend" },
  { "from": 100, "to": 208, "type": "friend" },
  { "from": 101, "to": 209, "type": "friend" },
  { "from": 206, "to": 102, "type": "friend" },
  { "from": 104, "to": 100, "type": "friend" },
  { "from": 104, "to": 108, "type": "friend" },
  { "from": 108, "to": 209, "type": "friend" },
  { "from": 206, "to": 106, "type": "friend" },
  { "from": 204, "to": 105, "type": "friend" },
  { "from": 208, "to": 207, "type": "friend" },
  { "from": 102, "to": 108, "type": "friend" },
  { "from": 207, "to": 203, "type": "friend" },
  { "from": 203, "to": 106, "type": "friend" },
  { "from": 202, "to": 108, "type": "friend" },
  { "from": 201, "to": 203, "type": "friend" },
  { "from": 105, "to": 100, "type": "friend" },
  { "from": 100, "to": 109, "type": "friend" },
  { "from": 207, "to": 109, "type": "friend" },
  { "from": 103, "to": 203, "type": "friend" },
  { "from": 208, "to": 104, "type": "friend" },
  { "from": 105, "to": 104, "type": "friend" },
  { "from": 103, "to": 208, "type": "friend" },
  { "from": 203, "to": 107, "type": "boyfriend" },
  { "from": 107, "to": 203, "type": "girlfriend" },
  { "from": 208, "to": 109, "type": "boyfriend" },
  { "from": 109, "to": 208, "type": "girlfriend" },
  { "from": 106, "to": 205, "type": "girlfriend" },
  { "from": 205, "to": 106, "type": "boyfriend" },
  { "from": 103, "to": 209, "type": "girlfriend" },
  { "from": 209, "to": 103, "type": "boyfriend" },
  { "from": 201, "to": 102, "type": "boyfriend" },
  { "from": 102, "to": 201, "type": "girlfriend" },
  { "from": 206, "to": 100, "type": "boyfriend" },
  { "from": 100, "to": 206, "type": "girlfriend" }
]

On this page