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Indexes support efficient execution of queries in MongoDB. Without indexes, MongoDB must scan every document in a collection to return query results. If an appropriate index exists for a query, MongoDB uses the index to limit the number of documents it must scan.

Although indexes improve query performance, adding an index has negative performance impact for write operations. For collections with a high write-to-read ratio, indexes are expensive because each insert must also update any indexes.

If your application is repeatedly running queries on the same fields, you can create an index on those fields to improve performance. For example, consider the following scenarios:

Index Type
A human resources department often needs to look up employees by employee ID. You can create an index on the employee ID field to improve query performance.
Single Field Index

A salesperson often needs to look up client information by location. Location is stored in an embedded object with fields like state, city, and zipcode. You can create an index on the location object to improve performance for queries on that object.


When you create an index on an embedded document, only queries that specify the entire embedded document use the index. Queries on a specific field within the document do not use the index.

Single Field Index on an embedded document
A grocery store manager often needs to look up inventory items by name and quantity to determine which items are low stock. You can create a single index on both the item and quantity fields to improve query performance.

You can create and manage indexes in MongoDB Atlas, with a driver method, or with the MongoDB Shell. MongoDB Atlas is the fully managed service for MongoDB deployments in the cloud.

For deployments hosted in MongoDB Atlas, you can create and manage indexes with the MongoDB Atlas UI or the Atlas CLI. MongoDB Atlas also includes a Performance Advisor that recommends indexes to improve slow queries, ranks suggested indexes by impact, and recommends which indexes to drop.

To learn how to create and manage indexes the MongoDB Atlas UI or the Atlas CLI, see Create, View, Drop, and Hide Indexes.

To learn more about the MongoDB Atlas Performance Advisor, see Monitor and Improve Slow Queries.

You can create and manage indexes with a driver method or the MongoDB Shell. To learn more, see the following resources:

Indexes are special data structures that store a small portion of the collection's data set in an easy-to-traverse form. MongoDB indexes use a B-tree data structure.

The index stores the value of a specific field or set of fields, ordered by the value of the field. The ordering of the index entries supports efficient equality matches and range-based query operations. In addition, MongoDB can return sorted results using the ordering in the index.

Certain restrictions apply to indexes, such as the length of the index keys or the number of indexes per collection. For details, see Index Limitations.

MongoDB creates a unique index on the _id field during the creation of a collection. The _id index prevents clients from inserting two documents with the same value for the _id field. You cannot drop this index.


In sharded clusters, if you do not use the _id field as the shard key, then your application must ensure the uniqueness of the values in the _id field. You can do this by using a field with an auto-generated ObjectId.

The default name for an index is the concatenation of the indexed keys and each key's direction in the index (1 or -1) using underscores as a separator. For example, an index created on { item : 1, quantity: -1 } has the name item_1_quantity_-1.

You cannot rename an index once created. Instead, you must drop and recreate the index with a new name.

To learn how to specify the name for an index, see Specify an Index Name.

Applications may encounter reduced performance during index builds, including limited read/write access to the collection. For more information on the index build process, see Index Builds on Populated Collections, including the Index Builds in Replicated Environments section.


Map-Reduce to Aggregation Pipeline


Create an Index