MongoDB
Atlas Search

MongoDB Atlas Search makes it easy to build fast, relevant, full-text search capabilities on top of your data in the cloud. Available exclusively with MongoDB Atlas.

SEARCH SIMPLIFIED

An integrated MongoDB full-text
search engine

Take advantage of advanced search capabilities built for the MongoDB document model, all with no additional infrastructure to manage.

Integrated and fully managed

Build search directly in MongoDB Atlas and remove the need to replicate your data elsewhere. With Atlas Search, you don’t need to set up, maintain, and scale a separate search platform.

Learn more about MongoDB Cloud →

Simple to use

Create a search index on your collections in a few clicks or a single API call. Test search queries and preview results in the Aggregation Pipeline Builder before deploying them in application code.

Rich search capabilities

Atlas Search brings together the best of both worlds. It’s deeply integrated with the MongoDB aggregation framework and is built on top of Apache Lucene, the industry standard library for full-text search.

"Atlas Search makes it easy for us to build features that help our users find what they need. Since it sits directly on top of our data, there's minimal infrastructure for our team to manage. It's fast and flexible, and we're excited to find new ways to implement it within our application."

Trevor Marshall, Current

“We’re planning to move all of our search functionality to use Atlas Search. The ability to have a built-in full-text search engine for our data without any additional infrastructure to manage is incredibly valuable and one more reason why we will continue to invest in Atlas as a core technology in our stack.”

Zac Rosenbauer, Precognitive

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"Atlas Search makes it easy for us to build features that help our users find what they need. Since it sits directly on top of our data, there's minimal infrastructure for our team to manage. It's fast and flexible, and we're excited to find new ways to implement it within our application."

Trevor Marshall, Current

“We’re planning to move all of our search functionality to use Atlas Search. The ability to have a built-in full-text search engine for our data without any additional infrastructure to manage is incredibly valuable and one more reason why we will continue to invest in Atlas as a core technology in our stack.”

Zac Rosenbauer, Precognitive

Read more

“All of our search is powered by MongoDB’s own Atlas Search. It’s so much easier and more efficient to use functionality that’s fully integrated with the database instead of separate services with their own costs. We always look at what’s new with MongoDB and see how we can use it to help scale our online services.”

Ryan O’Connell, Humanitix

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SEARCH IN ACTION

From A to Autocomplete

Design and deliver rich user experiences in your applications with built-in search features, made for MongoDB data.
Atlas Search is available on all clusters running MongoDB 4.2 or higher.

Typo Tolerance

Implement fuzzy search to surface relevant results, regardless of user input errors.

Autocomplete

Fill-in-the-blanks as users type to suggest common queries and search results.

Filters & Facets

Make information easier to discover with flexible ways to slice and dice search results.

Custom Scoring

Surface the right search results by adjusting search term relevance or boosting promoted content.

Synonyms

Define similar search terms to improve results and help people find the content they want

Rich Query DSL

Combine dozens of operators and options to build sophisticated search queries and aggregations.

Ready to build with Atlas Search?

Launch your first Atlas cluster in minutes.

Sign up for MongoDB Atlas

Create a MongoDB Atlas account and deploy your first cluster on AWS, Azure, or Google Cloud.

Build an Atlas Search Index

Create your first search index definition in a few clicks in the Atlas UI or a single Atlas API call.

Write a Search Query

Combine $search with other MongoDB stages and operators to query your database and get relevant results.

MongoDB Atlas Search FAQ

Full-text search uses a different structure for storing data that’s optimized for efficient search queries called an inverted index. Think of an inverted index as a glossary that lists all the unique values that appear in a document. Each value has a list of the documents in which it appears and the value’s position within that document.

Is Atlas Search only available with MongoDB Atlas?

Yes, Atlas Search is only available for MongoDB Atlas clusters running MongoDB 4.2 or higher.

Atlas Search supports multiple features, including:

  • Full-text search
  • Fuzzy search
  • Autocomplete
  • Highlighting
  • Custom analyzers
  • Custom scoring
  • Synonyms

If you have ideas or suggestions for other features, please submit them to our feedback portal.

Atlas Search currently supports text, dates, numerics, boolean, objectID, and geospatial data types.

Atlas Search currently supports over 40 languages using Lucene analyzers. You can see the full list in our documentation.

How do I use Atlas Search in MongoDB Atlas?

Atlas Search is available with all MongoDB Atlas clusters running MongoDB 4.2 or higher. It comes at no extra cost, although it will consume resources on your cluster.

Once you load data into an Atlas cluster, you can easily create search index definitions in the Atlas UI. You can also create, update, and delete indexes programmatically using the Atlas API.

How do I use Atlas Search as part of the MongoDB aggregation pipeline?

Atlas Search queries are MongoDB aggregation pipelines that use $search as the first stage. The $search stage can be customized using different operators and options. To learn more, visit our documentation.

What is the difference between Atlas Search and native MongoDB text indexes?

MongoDB offers native text search that supports basic queries on string content. However, text indexes only work for text-based content and the $text operator can be modified in limited ways.

In comparison, MongoDB Atlas Search offers:

  • Better results.

    Atlas Search can provide more ways to fine-tune the relevance of search results and support faster query results because it’s based on Apache Lucene, the open source search engine that powers Elasticsearch and Solr.

  • A rich feature set.

    Atlas Search offers support for over 40 languages, multiple data types, autocomplete, fuzzy search, custom analyzers, custom scoring, highlighting, synonyms, and more.

  • Open potential.

    Atlas Search has an active roadmap that will expand the features and use cases it can support. No additional work is planned to improve the native MongoDB text search, which was last updated in 2015 with MongoDB 3.2.

MongoDB Atlas SearchMongoDB Text Search
Supported deploymentsAtlas on AWS, Azure, GCPAll MongoDB deployments
Supported versions4.2 or higher3.2 or higher1
Consistency between base data and text indexEventually consistentStrongly consistent
Maximum numbers of indexes per collectionMultipleOne
Dynamic and static field mappingsYesNo
Field path to be searchedDefined at search timeDefined at index creation time
Search query performanceHigherLower
Integration with aggregation pipeline
Navigate, limit, skip, sort and filter results
Fully integratedFully integrated
Support for multiple data types
Text, numerics, dates, geoJSON, boolean, objectID
YesNo
Support for fuzzy searchYesNo
Support for autocompleteYesNo
Support for highlightingYesNo
Support for Lucene analyzers
Standard, Simple, Whitespace, Language, Keyword
YesNo
Supported languages362153
  1. For version 3 of the text index. MongoDB 2.4 can only support version 1, MongoDB 2.6 and 3.0 can support version 1 or 2.
  2. Arabic, Armenian, Basque, Bengali, Brazilian, Bulgarian, Catalan, CJK (Chinese, Japanese, Korean), Czech, Danish, Dutch, English, Finnish, French, Galician, German, Greek, Hindi, Hungarian, Indonesian, Irish, Italian, Latvian, Lithuanian, Norwegian, Persian, Portuguese, Romanian, Russian, Sorani, Spanish, Swedish, Turkish, Thai. See Docs
  3. Danish, Dutch, English, Finnish, French, German, Hungarian, Italian, Norwegian, Portuguese, Romanian, Russian, Spanish, Swedish, Turkish. See Docs

How does Atlas Search compare to Elasticsearch, Apache Solr, or Algolia?

Atlas Search has many of the same features as Elasticsearch, Apache Solr, Algolia, and other full-text search solutions. The key difference is that it’s fully managed and deeply integrated with the MongoDB document model and MongoDB Atlas. With Atlas Search, you can easily build rich search functionality without the need to replicate your data elsewhere.

Check out our documentation for tutorials and other resources on Atlas Search.