Indexing policies in Azure Cosmos DB

APPLIES TO: NoSQL

In Azure Cosmos DB, every container has an indexing policy that dictates how the container's items should be indexed. The default indexing policy for newly created containers indexes every property of every item and enforces range indexes for any string or number. This allows you to get good query performance without having to think about indexing and index management upfront.

In some situations, you might want to override this automatic behavior to better suit your requirements. You can customize a container's indexing policy by setting its indexing mode, and include or exclude property paths.

Indexing mode

Azure Cosmos DB supports two indexing modes:

• Consistent: The index is updated synchronously as you create, update, or delete items. This means that the consistency of your read queries will be the consistency configured for the account.
• None: Indexing is disabled on the container. This mode is commonly used when a container is used as a pure key-value store without the need for secondary indexes. It can also be used to improve the performance of bulk operations. After the bulk operations are complete, the index mode can be set to Consistent and then monitored using the IndexTransformationProgress until complete.

By default, indexing policy is set to automatic. It's achieved by setting the automatic property in the indexing policy to true. Setting this property to true allows Azure Cosmos DB to automatically index items as they're written.

Index size

In Azure Cosmos DB, the total consumed storage is the combination of both the Data size and Index size. The following are some features of index size:

• The index size depends on the indexing policy. If all the properties are indexed, then the index size can be larger than the data size.
• When data is deleted, indexes are compacted on a near continuous basis. However, for small data deletions, you might not immediately observe a decrease in index size.
• The Index size can temporarily grow when physical partitions split. The index space is released after the partition split is completed.

Including and excluding property paths

A custom indexing policy can specify property paths that are explicitly included or excluded from indexing. By optimizing the number of paths that are indexed, you can substantially reduce the latency and RU charge of write operations. These paths are defined following the method described in the indexing overview section with the following additions:

• a path leading to a scalar value (string or number) ends with /?
• elements from an array are addressed together through the /[] notation (instead of /0, /1 etc.)
• the /* wildcard can be used to match any elements below the node

Taking the same example again:

    {
        "locations": [
            { "country": "Germany", "city": "Berlin" },
            { "country": "France", "city": "Paris" }
        ],
        "headquarters": { "country": "Belgium", "employees": 250 },
        "exports": [
            { "city": "Moscow" },
            { "city": "Athens" }
        ]
    }

• the headquarters's employees path is /headquarters/employees/?

• the locations' country path is /locations/[]/country/?

• the path to anything under headquarters is /headquarters/*

For example, we could include the /headquarters/employees/? path. This path would ensure that we index the employees property but wouldn't index extra nested JSON within this property.

Include/exclude strategy

Any indexing policy has to include the root path /* as either an included or an excluded path.

• Include the root path to selectively exclude paths that don't need to be indexed. This approach is recommended as it lets Azure Cosmos DB proactively index any new property that might be added to your model.

• Exclude the root path to selectively include paths that need to be indexed. The partition key property path isn't indexed by default with the exclude strategy and should be explicitly included if needed.

• For paths with regular characters that include: alphanumeric characters and _ (underscore), you don't have to escape the path string around double quotes (for example, "/path/?"). For paths with other special characters, you need to escape the path string around double quotes (for example, "/"path-abc"/?"). If you expect special characters in your path, you can escape every path for safety. Functionally, it doesn't make any difference if you escape every path or just the ones that have special characters.

• The system property _etag is excluded from indexing by default, unless the etag is added to the included path for indexing.

• If the indexing mode is set to consistent, the system properties id and _ts are automatically indexed.

• If an explicitly indexed path doesn't exist in an item, a value is added to the index to indicate that the path is undefined.

All explicitly included paths have values added to the index for each item in the container, even if the path is undefined for a given item.

See this section for indexing policy examples for including and excluding paths.

Include/exclude precedence

If your included paths and excluded paths have a conflict, the more precise path takes precedence.

Here's an example:

Included Path: /food/ingredients/nutrition/*

Excluded Path: /food/ingredients/*

In this case, the included path takes precedence over the excluded path because it's more precise. Based on these paths, any data in the food/ingredients path or nested within would be excluded from the index. The exception would be data within the included path: /food/ingredients/nutrition/*, which would be indexed.

Here are some rules for included and excluded paths precedence in Azure Cosmos DB:

• Deeper paths are more precise than narrower paths. for example: /a/b/? is more precise than /a/?.

• The /? is more precise than /*. For example /a/? is more precise than /a/* so /a/? takes precedence.

• The path /* must be either an included path or excluded path.

Full text indexes

Full text indexes enable full text search and scoring efficiently using the index. Defining a full text path in an indexing policy can easily be done by including a fullTextIndexes section of the indexing policy that contains all of the text paths to be indexed. For example:

{
    "indexingMode": "consistent",
    "automatic": true,
    "includedPaths": [
        {
            "path": "/*"
        }
    ],
    "excludedPaths": [
        {
            "path": "/\"_etag\"/?"
        },
    ],
    "fullTextIndexes": [
        {
            "path": "/text"
        }
    ]
}

Vector indexes

Vector indexes increase the efficiency when performing vector searches using the VectorDistance system function. Vectors searches have lower latency, higher throughput, and less RU consumption when applying a vector index. You can specify the following types of vector index policies:

Type	Description	Max dimensions
flat	Stores vectors on the same index as other indexed properties.	505
quantizedFlat	Quantizes (compresses) vectors before storing on the index. This can improve latency and throughput at the cost of a small amount of accuracy.	4096
diskANN	Creates an index based on DiskANN for fast and efficient approximate search.	4096

A few points to note:

• The flat and quantizedFlat index types apply Azure Cosmos DB's index to store and read each vector when performing a vector search. Vector searches with a flat index are brute-force searches and produce 100% accuracy or recall. That is, it's guaranteed to find the most similar vectors in the dataset. However, there's a limitation of 505 dimensions for vectors on a flat index.

  • The quantizedFlat index stores quantized (compressed) vectors on the index. Vector searches with quantizedFlat index are also brute-force searches, however their accuracy might be slightly less than 100% since the vectors are quantized before adding to the index. However, vector searches with quantized flat should have lower latency, higher throughput, and lower RU cost than vector searches on a flat index. This is a good option for scenarios where you're using query filters to narrow down the vector search to a relatively small set of vectors, and high accuracy is required.

  • The diskANN index is a separate index defined specifically for vectors applying DiskANN, a suite of high performance vector indexing algorithms developed by Microsoft Research. DiskANN indexes can offer some of the lowest latency, highest throughput, and lowest RU cost queries, while still maintaining high accuracy. However, since DiskANN is an approximate nearest neighbors (ANN) index, the accuracy might be lower than quantizedFlat or flat.

The diskANN and quantizedFlat indexes can take optional index build parameters that can be used to tune the accuracy versus latency trade-off that applies to every Approximate Nearest Neighbors vector index.

• quantizationByteSize: Sets the size (in bytes) for product quantization. Min=1, Default=dynamic (system decides), Max=512. Setting this larger may result in higher accuracy vector searches at expense of higher RU cost and higher latency. This applies to both quantizedFlat and DiskANN index types.
  • indexingSearchListSize: Sets how many vectors to search over during index build construction. Min=10, Default=100, Max=500. Setting this larger may result in higher accuracy vector searches at the expense of longer index build times and higher vector ingest latencies. This applies to DiskANN indexes only.

Here's an example of an indexing policy with a vector index:

{
    "indexingMode": "consistent",
    "automatic": true,
    "includedPaths": [
        {
            "path": "/*"
        }
    ],
    "excludedPaths": [
        {
            "path": "/_etag/?",
        },
        {
            "path": "/vector/*"
        }
    ],
    "vectorIndexes": [
        {
            "path": "/vector",
            "type": "diskANN"
        }
    ]
}

Spatial indexes

When you define a spatial path in the indexing policy, you should define which index type should be applied to that path. Possible types for spatial indexes include:

• Point

• Polygon

• MultiPolygon

• LineString

Azure Cosmos DB, by default, won't create any spatial indexes. If you would like to use spatial SQL built-in functions, you should create a spatial index on the required properties. See this section for indexing policy examples for adding spatial indexes.

Tuple indexes

Tuple Indexes are useful when performing filtering on multiple fields within an array element. Tuple indexes are defined in the includedPaths section of the indexing policy using the tuple specifier “[]”.

Array tuple paths will be defined in the includedPaths section and will be using the following notation.

<path prefix>/[]/{<tuple 1>, <tuple 2> … <tuple n>}/?

Note that:

• The first part, the path Prefix, is the path that is common between the tuples. It is the path from root to array. In our example it is “/events”.
• Next is the array wildcard specifier “[]”. All array tuple paths should have an array wildcard specifier before the tuple specifier “{}”.
• Next is specifying the tuples using the tuple specifier “{}”.
• Tuples will be separated by comma.
• Tuple needs to use the same path specification as other index paths with a few exceptions:
• Tuples should not start with the leading “/”.
• Tuples should not have array wildcards.
• Tuples should not end “?” or “*”
• “?” is the last segment in a tuple path and should be specified immediately after the tuple specifier segment.

For example,

/events/[]/{name, category}/?

These are a few examples of valid array tuple paths:

    “includedPaths”:[  
        {“path”: “/events/[]/{name/first, name/last}/?”}, 
        {“path”: “/events/[]/{name/first, category}/?”}, 
        {“path”: “/events/[]/{name/first, category/subcategory}/?”}, 
        {“path”: “/events/[]/{name/[1]/first, category}/?”}, 
        {“path”: “/events/[]/{[1], [3]}/?”}, 
        {“path”: “/city/[1]/events/[]/{name, category}/?”} 
    ]

These are a few examples of invalid array tuple paths

• /events/[]/{name/[]/first, category}/?
  • One of the tuples has array wildcard
• /events/[]/{name, category}/*
  • The last segment in array tuple path should be “?” and not *
• /events/[]/{{name, first},category}/?
  • The tuple specifier is nested
• /events/{name, category}/?
  • The array wildcard is missing before the tuple specifier
• /events/[]/{/name,/category}/?
  • Tuples start with leading /
• /events/[]/{name/?,category/?}/?
  • Tuples end with an ?
• /city/[]/events/[]/{name, category}/?
  • The path prefix as 2 array wildcards

Composite indexes

Queries that have an ORDER BY clause with two or more properties require a composite index. You can also define a composite index to improve the performance of many equality and range queries. By default, no composite indexes are defined so you should add composite indexes as needed.

Unlike with included or excluded paths, you can't create a path with the /* wildcard. Every composite path has an implicit /? at the end of the path that you don't need to specify. Composite paths lead to a scalar value that is the only value included in the composite index. If a path in a composite index doesn't exist in an item or leads to a nonscalar value, a value is added to the index to indicate that the path is undefined.

When defining a composite index, you specify:

• Two or more property paths. The sequence in which property paths are defined matters.

• The order (ascending or descending).

ORDER BY queries on multiple properties:

The following considerations are used when using composite indexes for queries with an ORDER BY clause with two or more properties.

• If the composite index paths don't match the sequence of the properties in the ORDER BY clause, then the composite index can't support the query.

• The order of composite index paths (ascending or descending) should also match the order in the ORDER BY clause.

• The composite index also supports an ORDER BY clause with the opposite order on all paths.

Consider the following example where a composite index is defined on properties name, age, and _ts:

Composite Index	Sample ORDER BY Query	Supported by Composite Index?
(name ASC, age ASC)	SELECT * FROM c ORDER BY c.name ASC, c.age asc	Yes
(name ASC, age ASC)	SELECT * FROM c ORDER BY c.age ASC, c.name asc	No
(name ASC, age ASC)	SELECT * FROM c ORDER BY c.name DESC, c.age DESC	Yes
(name ASC, age ASC)	SELECT * FROM c ORDER BY c.name ASC, c.age DESC	No
(name ASC, age ASC, timestamp ASC)	SELECT * FROM c ORDER BY c.name ASC, c.age ASC, timestamp ASC	Yes
(name ASC, age ASC, timestamp ASC)	SELECT * FROM c ORDER BY c.name ASC, c.age ASC	No

You should customize your indexing policy so you can serve all necessary ORDER BY queries.

Queries with filters on multiple properties

If a query has filters on two or more properties, it might be helpful to create a composite index for these properties.

For example, consider the following query that has both an equality and range filter:

SELECT *
FROM c
WHERE c.name = "John" AND c.age > 18

This query is more efficient, taking less time and consuming fewer RUs, if it's able to apply a composite index on (name ASC, age ASC).

Queries with multiple range filters can also be optimized with a composite index. However, each individual composite index can only optimize a single range filter. Range filters include >, <, <=, >=, and !=. The range filter should be defined last in the composite index.

Consider the following query with an equality filter and two range filters:

SELECT *
FROM c
WHERE c.name = "John" AND c.age > 18 AND c._ts > 1612212188

This query is more efficient with a composite index on (name ASC, age ASC) and (name ASC, _ts ASC). However, the query wouldn't utilize a composite index on (age ASC, name ASC) because the properties with equality filters must be defined first in the composite index. Two separate composite indexes are required instead of a single composite index on (name ASC, age ASC, _ts ASC) since each composite index can only optimize a single range filter.

The following considerations are used when creating composite indexes for queries with filters on multiple properties

• Filter expressions can use multiple composite indexes.
• The properties in the query's filter should match those in composite index. If a property is in the composite index but isn't included in the query as a filter, the query won't utilize the composite index.
• If a query has other properties in the filter that aren't defined in a composite index, then a combination of composite and range indexes are used to evaluate the query. This requires fewer RUs than exclusively using range indexes.
• If a property has a range filter (>, <, <=, >=, or !=), then this property should be defined last in the composite index. If a query has more than one range filter, it might benefit from multiple composite indexes.
• When creating a composite index to optimize queries with multiple filters, the ORDER of the composite index has no impact on the results. This property is optional.

Consider the following examples where a composite index is defined on properties name, age, and timestamp:

Composite Index	Sample Query	Supported by Composite Index?
(name ASC, age ASC)	SELECT * FROM c WHERE c.name = "John" AND c.age = 18	Yes
(name ASC, age ASC)	SELECT * FROM c WHERE c.name = "John" AND c.age > 18	Yes
(name ASC, age ASC)	SELECT COUNT(1) FROM c WHERE c.name = "John" AND c.age > 18	Yes
(name DESC, age ASC)	SELECT * FROM c WHERE c.name = "John" AND c.age > 18	Yes
(name ASC, age ASC)	SELECT * FROM c WHERE c.name != "John" AND c.age > 18	No
(name ASC, age ASC, timestamp ASC)	SELECT * FROM c WHERE c.name = "John" AND c.age = 18 AND c.timestamp > 123049923	Yes
(name ASC, age ASC, timestamp ASC)	SELECT * FROM c WHERE c.name = "John" AND c.age < 18 AND c.timestamp = 123049923	No
(name ASC, age ASC) and (name ASC, timestamp ASC)	SELECT * FROM c WHERE c.name = "John" AND c.age < 18 AND c.timestamp > 123049923	Yes

Queries with a filter and ORDER BY

If a query filters on one or more properties and has different properties in the ORDER BY clause, it might be helpful to add the properties in the filter to the ORDER BY clause.

For example, by adding the properties in the filter to the ORDER BY clause, the following query could be rewritten to apply a composite index:

Query using range index:

SELECT *
FROM c 
WHERE c.name = "John" 
ORDER BY c.timestamp

Query using composite index:

SELECT * 
FROM c 
WHERE c.name = "John"
ORDER BY c.name, c.timestamp

The same query optimizations can be generalized for any ORDER BY queries with filters, keeping in mind that individual composite indexes can only support, at most, one range filter.

Query using range index:

SELECT * 
FROM c 
WHERE c.name = "John" AND c.age = 18 AND c.timestamp > 1611947901 
ORDER BY c.timestamp

Query using composite index:

SELECT * 
FROM c 
WHERE c.name = "John" AND c.age = 18 AND c.timestamp > 1611947901 
ORDER BY c.name, c.age, c.timestamp

In addition, you can use composite indexes to optimize queries with system functions and ORDER BY:

Query using range index:

SELECT * 
FROM c 
WHERE c.firstName = "John" AND Contains(c.lastName, "Smith", true) 
ORDER BY c.lastName

Query using composite index:

SELECT * 
FROM c 
WHERE c.firstName = "John" AND Contains(c.lastName, "Smith", true) 
ORDER BY c.firstName, c.lastName

The following considerations apply when creating composite indexes to optimize a query with a filter and ORDER BY clause:

• If you don't define a composite index on a query with a filter on one property and a separate ORDER BY clause using a different property, the query will still succeed. However, the RU cost of the query can be reduced with a composite index, particularly if the property in the ORDER BY clause has a high cardinality.
• If the query filters on properties, these properties should be included first in the ORDER BY clause.
• If the query filters on multiple properties, the equality filters must be the first properties in the ORDER BY clause.
• If the query filters on multiple properties, you can have a maximum of one range filter or system function utilized per composite index. The property used in the range filter or system function should be defined last in the composite index.
• All considerations for creating composite indexes for ORDER BY queries with multiple properties and queries with filters on multiple properties still apply.

Composite Index	Sample ORDER BY Query	Supported by Composite Index?
(name ASC, timestamp ASC)	SELECT * FROM c WHERE c.name = "John" ORDER BY c.name ASC, c.timestamp ASC	Yes
(name ASC, timestamp ASC)	SELECT * FROM c WHERE c.name = "John" AND c.timestamp > 1589840355 ORDER BY c.name ASC, c.timestamp ASC	Yes
(timestamp ASC, name ASC)	SELECT * FROM c WHERE c.timestamp > 1589840355 AND c.name = "John" ORDER BY c.timestamp ASC, c.name ASC	No
(name ASC, timestamp ASC)	SELECT * FROM c WHERE c.name = "John" ORDER BY c.timestamp ASC, c.name ASC	No
(name ASC, timestamp ASC)	SELECT * FROM c WHERE c.name = "John" ORDER BY c.timestamp ASC	No
(age ASC, name ASC, timestamp ASC)	SELECT * FROM c WHERE c.age = 18 and c.name = "John" ORDER BY c.age ASC, c.name ASC,c.timestamp ASC	Yes
(age ASC, name ASC, timestamp ASC)	SELECT * FROM c WHERE c.age = 18 and c.name = "John" ORDER BY c.timestamp ASC	No

Queries with a filter and an aggregate

If a query filters on one or more properties and has an aggregate system function, it might be helpful to create a composite index for the properties in the filter and aggregate system function. This optimization applies to the SUM and AVG system functions.

The following considerations apply when creating composite indexes to optimize a query with a filter and aggregate system function.

• Composite indexes are optional when running queries with aggregates. However, the RU cost of the query can often be reduced with a composite index.
• If the query filters on multiple properties, the equality filters must be the first properties in the composite index.
• You can have a maximum of one range filter per composite index and it must be on the property in the aggregate system function.
• The property in the aggregate system function should be defined last in the composite index.
• The order (ASC or DESC) doesn't matter.

Composite Index	Sample Query	Supported by Composite Index?
(name ASC, timestamp ASC)	SELECT AVG(c.timestamp) FROM c WHERE c.name = "John"	Yes
(timestamp ASC, name ASC)	SELECT AVG(c.timestamp) FROM c WHERE c.name = "John"	No
(name ASC, timestamp ASC)	SELECT AVG(c.timestamp) FROM c WHERE c.name > "John"	No
(name ASC, age ASC, timestamp ASC)	SELECT AVG(c.timestamp) FROM c WHERE c.name = "John" AND c.age = 25	Yes
(age ASC, timestamp ASC)	SELECT AVG(c.timestamp) FROM c WHERE c.name = "John" AND c.age > 25	No

Composite indexes with an array wildcard

Below is an example for a composite index that contains an array wildcard.

{  
    "automatic":true,
    "indexingMode":"Consistent",
    "includedPaths":[  
        {  
            "path":"/*"
        }
    ],
    "excludedPaths":[],
    "compositeIndexes":[  
        [  
            {"path":"/familyname", "order":"ascending"},
            {"path":"/children/[]/age", "order":"descending"}
        ]
    ]
}

An example query that can benefit from this composite index is:

SELECT r.id
FROM root r
JOIN ch IN r.children
WHERE r.familyname = 'Anderson' AND ch.age > 20

Modifying the indexing policy

A container's indexing policy can be updated at any time by using the Azure portal or one of the supported SDKs. An update to the indexing policy triggers a transformation from the old index to the new one, which is performed online and in-place (so no extra storage space is consumed during the operation). The old indexing policy is efficiently transformed to the new policy without affecting the write availability, read availability, or the throughput provisioned on the container. Index transformation is an asynchronous operation, and the time it takes to complete depends on the provisioned throughput, the number of items and their size. If multiple indexing policy updates have to be made, it's recommended to do all the changes as a single operation in order to have the index transformation complete as quickly as possible.

There's no impact to write availability during any index transformations. The index transformation uses your provisioned RUs but at a lower priority than your CRUD operations or queries.

There's no impact to read availability when adding new indexed paths. Queries will only utilize new indexed paths once an index transformation is complete. In other words, when adding a new indexed path, queries that benefit from that indexed path has the same performance before and during the index transformation. After the index transformation is complete, the query engine will begin to use the new indexed paths.

When removing indexed paths, you should group all your changes into one indexing policy transformation. If you remove multiple indexes and do so in one single indexing policy change, the query engine provides consistent and complete results throughout the index transformation. However, if you remove indexes through multiple indexing policy changes, the query engine won't provide consistent or complete results until all index transformations complete. Most developers don't drop indexes and then immediately try to run queries that utilize these indexes so, in practice, this situation is unlikely.

When you drop an indexed path, the query engine will immediately stop using it, and will do a full scan instead.

Indexing policies and TTL

Using the Time-to-Live (TTL) feature requires indexing. This means that:

• it isn't possible to activate TTL on a container where the indexing mode is set to none,
• it isn't possible to set the indexing mode to None on a container where TTL is activated.

For scenarios where no property path needs to be indexed, but TTL is required, you can use an indexing policy with an indexing mode set to consistent, no included paths, and /* as the only excluded path.

Related content

• Indexing overview
• How to manage indexing policy