FQL v4 will be decommissioned on June 30, 2025. Ensure that you complete your migration from FQL v4 to FQL v10 by that date.

For more details, see the v4 EOL announcement and migration guide. Contact support@fauna.com with any questions.

Indexes

An understanding of index creation and usage is crucial for effective Fauna development. Indexes allow for the organization and retrieval of documents by attributes other than their Reference. They act as a lookup table that improves the performance of finding documents: instead of reading every single document to find the one(s) that you are interested in, you query an index to find those documents. To learn more about how Fauna indexes work, see the Index tutorials. For examples of index creation and usage, see Index recipes.

See limits for details on concurrent index builds and transaction limits. See the CreateIndex reference page for limitations on what an index may be named.

Source

When you create an index, you specify its source, which is one or more collections of documents. Once the index is active, any query that creates, updates, or deletes a document in the source collection(s) causes the index to be updated.

Terms

An index can define terms: these are zero or more term objects that define which document fields to use for searching.

terms are comparable to column=value predicates in an SQL WHERE clause. For example, if your documents have a name field, you can define terms to include that field, and then you can find all of the documents that match a name.

Only scalar Values are indexed. When a term targets a document field or index binding result that has an array, one index entry per array item is created, which makes it easy to search for an array item. Objects are not indexed. As a result, it is not possible to search for arrays or objects.

Be aware that when the terms definition includes multiple array fields, the number of index entries created is the Cartesian product of the number of array items. For example, when an index terms definition specifies two fields that are arrays, and a document is created including one array with 5 items and the second array with 11 items, 55 index entries are created. Index write operations are grouped together, so the billing impact depends on the overall size of the index entries.

When an index has one or more terms, the index is partitioned by the terms, allowing Fauna to efficiently scale indexes.

When a document is indexed, and all of the index’s defined terms evaluate to null, no index entry is stored for the document.

Values

An index can define values: these are zero or more scalar Values returned for each index entry that matches the terms when you query the index. values are comparable to the SQL SELECT clause.

values are also how indexes are sorted: each field value in values is sorted lexically according to the field type, and the order can be inverted by setting reverse: true.

Each index entry records the Reference of each document involved in the index. When there is no values definition, the index returns the Reference for each matching index entry. When values is defined, only the defined field values are returned.

When a document is indexed, and all of the index’s defined values evaluate to null, no index entry is stored for the document.

Values must refer to fields with scalar Values. Objects are not indexed, so when a values definition points to a document field or index binding result that has an Object, the index entry stores null because Objects cannot be sorted. When a values definition points to a document field or index binding result that has an Array, one index entry per array item is created.

Collection index

An index with no terms and values specified is known as a collection index: searching for specific documents is not possible, and all documents within the collection are included in the result set, and are sorted by their reference in ascending order.

Unique

You can specify that an index is unique. This means that, for the defined terms and values, the index contains only one entry for a document having those specific terms and values. As a result, creating or updating a document to have the same terms and values as an existing document would cause an error.

Avoid creating a unique index that does not define terms.

If you do create a "term-less" index, the index could cause performance issues. Every time a covered document is created or updated, the index (and its history) needs to be evaluated to decide whether the document is unique or not. As the index grows larger, the evaluation for uniqueness can cause your queries involving writes to exceed the query timeout.

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