MongoDB Search Query Performance

For the complete MongoDB documentation index, see www.mongodb.com/docs/llms.txt

MongoDB Search Query Performance

Improve your MongoDB Search query performance by understanding how query complexity, operators, and aggregation pipeline stages affect cluster performance. Use the recommendations below to structure queries efficiently for your deployment type.

Consider Query Operators and Query Complexity

The complexity level of MongoDB Search queries and the type of [operators](https://www.mongodb.com/docs/search/query/operators-collectors/overview.md#std-label-fts-operators used can affect database performance for the node that mongot runs on.

Highly complex queries, such as queries with multiple clauses that use the [compound](https://www.mongodb.com/docs/search/query/operators-collectors/compound.md#std-label-compound-ref operator, or queries which use the [regex](https://www.mongodb.com/docs/search/query/operators-collectors/regex.md#std-label-regex-ref (regular expression) or the [wildcard](https://www.mongodb.com/docs/search/query/operators-collectors/wildcard.md#std-label-wildcard-ref operator, are resource-intensive.

Compound Queries

If your query includes multiple nested [compound](https://www.mongodb.com/docs/search/query/operators-collectors/compound.md#std-label-compound-ref statements, ensure that these are not redundant. If the clauses are added programmatically, consider implementing the logic in the application to avoid inclusion of redundant clauses in the queries. Every score calculation per field that mongot performs, such as for the must and should clauses, increases execution time. To optimize performance, place non-scoring operators such as [equals](https://www.mongodb.com/docs/search/query/operators-collectors/equals.md#std-label-equals-ref, [range](https://www.mongodb.com/docs/search/query/operators-collectors/range.md#std-label-range-ref, and [in](https://www.mongodb.com/docs/search/query/operators-collectors/in.md#std-label-in-ref in the [filter](https://www.mongodb.com/docs/search/query/operators-collectors/compound.md#mongodb-data-filter clause to avoid unnecessary scoring operations.

You can use the MongoDB Search [facet (MongoDB Search Operator)](https://www.mongodb.com/docs/search/query/operators-collectors/facet.md#std-label-fts-facet-ref collector to extract metadata and avoid running multiple queries for search results and metadata. You can use $search.facet to retrieve both documents and metadata in a single query. If you only need metadata, use $searchMeta.facet to avoid document lookup. For an example, see the [Metadata and Search Results example.](https://www.mongodb.com/docs/search/query/operators-collectors/facet.md#std-label-fts-facet-egs

Use $limit Before $facet

Using a [$limit](https://www.mongodb.com/docs/manual/reference/operator/aggregation/limit.md#mongodb-pipeline-pipe.-limit aggregation pipeline stage after a [$facet](https://www.mongodb.com/docs/manual/reference/operator/aggregation/facet.md#mongodb-pipeline-pipe.-facet aggregation pipeline stage might negatively impact query performance. To avoid performance bottlenecks, use [$limit](https://www.mongodb.com/docs/manual/reference/operator/aggregation/limit.md#mongodb-pipeline-pipe.-limit before [$facet.](https://www.mongodb.com/docs/manual/reference/operator/aggregation/facet.md#mongodb-pipeline-pipe.-facet

Example:

{
  {
    "$search": {...}
  },
  { "$limit": 20 },
  {
    "$facet": {
      "results": [],
      "totalCount": $$SEARCH_META
    }
  }
}

For a demonstration, see the following examples:

  • [Metadata and Search Results Example](https://www.mongodb.com/docs/search/query/operators-collectors/facet.md#std-label-fts-facet-egs

  • [Facet Example](https://www.mongodb.com/docs/search/query/counting.md#std-label-fts-count-aggregation-variable

Minimize Additional MQL Aggregation Stages

Try to encapsulate the entire search logic within the $search stage itself and minimize using additional blocking stages, such as [$group](https://www.mongodb.com/docs/manual/reference/operator/aggregation/group.md#mongodb-pipeline-pipe.-group, [$count](https://www.mongodb.com/docs/manual/reference/operator/aggregation/count.md#mongodb-pipeline-pipe.-count, [$match](https://www.mongodb.com/docs/manual/reference/operator/aggregation/match.md#mongodb-pipeline-pipe.-match, or [$sort](https://www.mongodb.com/docs/manual/reference/operator/aggregation/sort.md#mongodb-pipeline-pipe.-sort. This optimizes the MongoDB Search index usage, and reduces the need for additional database operations in mongod.

Use compound.filter Instead of $match

For queries that require multiple filtering operations, use the [compound Operator](https://www.mongodb.com/docs/search/query/operators-collectors/compound.md#std-label-compound-ref operator with filter clauses. If you must use the [$match](https://www.mongodb.com/docs/manual/reference/operator/aggregation/match.md#mongodb-pipeline-pipe.-match stage in your aggregation pipeline, consider using the [storedSource](https://www.mongodb.com/docs/search/indexes/stored-source-definition.md#std-label-fts-stored-source-definition option to store only the fields that your [$match](https://www.mongodb.com/docs/manual/reference/operator/aggregation/match.md#mongodb-pipeline-pipe.-match condition needs. You can then use the [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search [returnStoredSource](https://www.mongodb.com/docs/search/query/return-stored-source.md#std-label-fts-return-stored-source-option option to retrieve stored fields and avoid the mongod full document lookup.

See also:

  • [Storing Source Fields](https://www.mongodb.com/docs/search/performance/index-performance.md#std-label-perf-ref-stored-source

  • [$match Example](https://www.mongodb.com/docs/search/query/return-stored-source.md#std-label-fts-return-stored-source-egs

Use facet Instead of $group

If you use [$group](https://www.mongodb.com/docs/manual/reference/operator/aggregation/group.md#mongodb-pipeline-pipe.-group to get basic counts for field aggregations, you can use [facet (MongoDB Search Operator)](https://www.mongodb.com/docs/search/query/operators-collectors/facet.md#std-label-fts-facet-ref inside the [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search stage. If you need only metadata results, you can use [facet (MongoDB Search Operator)](https://www.mongodb.com/docs/search/query/operators-collectors/facet.md#std-label-fts-facet-ref inside inside the [$searchMeta](https://www.mongodb.com/docs/search/query/aggregation-stages/searchmeta.md#mongodb-pipeline-pipe.-searchMeta stage instead.

Use count Instead of $count

If you use [$count](https://www.mongodb.com/docs/manual/reference/operator/aggregation/count.md#mongodb-pipeline-pipe.-count to get a count of the number of documents, we recommend that you use [count](https://www.mongodb.com/docs/search/query/counting.md#std-label-count-ref inside the [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search or [$searchMeta](https://www.mongodb.com/docs/search/query/aggregation-stages/searchmeta.md#mongodb-pipeline-pipe.-searchMeta stage instead.

Use sort, near, or returnStoredSource Instead of $sort

  • For sorting numeric, date, string, boolean, UUID, and objectID fields, use the sort option with the [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search stage. To learn more, see [Sort MongoDB Search Results.](https://www.mongodb.com/docs/search/query/sort.md#std-label-sort-ref

  • For sorting geo fields, use the [near](https://www.mongodb.com/docs/search/query/operators-collectors/near.md#std-label-near-ref operator.

  • To sort other fields, use $sort and [returnStoredSource](https://www.mongodb.com/docs/search/query/return-stored-source.md#std-label-fts-return-stored-source-option fields.

Using [$skip](https://www.mongodb.com/docs/manual/reference/operator/aggregation/skip.md#mongodb-pipeline-pipe.-skip and [$limit](https://www.mongodb.com/docs/manual/reference/operator/aggregation/limit.md#mongodb-pipeline-pipe.-limit to retrieve results non-sequentially might be slow if the results for your query are large. For optimal performance, use the [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search searchAfter or searchBefore options to paginate results. To learn more, see [Paginate the Results.](https://www.mongodb.com/docs/search/query/paginate-results.md#std-label-fts-paginate-results

To return non-sequential results, such as jumping from page 2 to page 5, you can use the following pipeline stages:

  • [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search searchAfter the last result on Page 2

  • [$skip](https://www.mongodb.com/docs/manual/reference/operator/aggregation/skip.md#mongodb-pipeline-pipe.-skip documents on Pages 3 and 4

  • [$limit](https://www.mongodb.com/docs/manual/reference/operator/aggregation/limit.md#mongodb-pipeline-pipe.-limit results for Page 5

Here, your query is optimized to skip only 2 pages of results, instead of skipping 4 pages if you didn't use searchAfter. For a demonstration of this, see [Paginate the Results.](https://www.mongodb.com/docs/search/query/paginate-results.md#std-label-fts-paginate-results

Use $search Instead of $text or $regex

For applications that rely heavily on MongoDB [$text](https://www.mongodb.com/docs/manual/reference/operator/query/text.md#mongodb-query-op.-text and [$regex](https://www.mongodb.com/docs/manual/reference/operator/query/regex.md#mongodb-query-op.-regex queries, use the following recommendations to determine whether to refactor your applications or migrate your applications to MongoDB Search [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search. The $search aggregation pipeline stage provides features that are either not available through the MongoDB operators or are available through the MongoDB operators but not as performant as MongoDB Search $search.

The following table shows how MongoDB [$regex](https://www.mongodb.com/docs/manual/reference/operator/query/regex.md#mongodb-query-op.-regex, [$text](https://www.mongodb.com/docs/manual/reference/operator/query/text.md#mongodb-query-op.-text, and MongoDB Search [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search address your application's requirements.

If your application requires... Use... Because...
Datastore to respect write concerns [$regex](https://www.mongodb.com/docs/manual/reference/operator/query/regex.md#mongodb-query-op.-regex For transactions with heavy reads after writes, we recommend [$regex](https://www.mongodb.com/docs/manual/reference/operator/query/regex.md#mongodb-query-op.-regex. For [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search, reads after writes should be rare.
Cluster optimized for write performance [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search indexes don't degrade cluster write performance.
Searching through large data sets [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search uses an inverted index, which enables fast document retrieval at very large scales.
Language awareness [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search supports many [language analyzers](https://www.mongodb.com/docs/search/indexes/analyzers/language.md#std-label-ref-language-analyzers that can tokenize (create searchable terms) languages, remove stopwords, and interpret diacritics for improved search relevance.
Case-insensitive text search [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search offers more capabilities than [$regex.](https://www.mongodb.com/docs/manual/reference/operator/query/regex.md#mongodb-query-op.-regex
Highlighting result text [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search [highlighting](https://www.mongodb.com/docs/search/query/highlighting.md#std-label-highlight-ref allows you to contextualize the documents in the results, which is essential for natural language queries.
Geospatial-aware search queries [$regex](https://www.mongodb.com/docs/manual/reference/operator/query/regex.md#mongodb-query-op.-regex or [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB [$regex](https://www.mongodb.com/docs/manual/reference/operator/query/regex.md#mongodb-query-op.-regex and MongoDB Search [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search treat geospatial parameters differently. In MongoDB, lines between coordinates are spherical, which is well-suited for coordinates for long distance such as air flight. MongoDB Search uses Lucene, which draws a straight line between coordinates and is well-suited for short distance.
Autocompletion of search queries [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search For autocomplete.
Fuzzy matching on text input [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search [text](https://www.mongodb.com/docs/search/query/operators-collectors/text.md#std-label-text-ref and [autocomplete](https://www.mongodb.com/docs/search/query/operators-collectors/autocomplete.md#std-label-autocomplete-ref operators support fuzzy matching to filter on input text and address misspelled words (typos).
Filtering based on multiple strings [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search [compound](https://www.mongodb.com/docs/search/query/operators-collectors/compound.md#std-label-compound-ref supports filtering based on multiple strings.
Relevance score sorted search [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search uses the BM25 algorithm for determining the search relevance score of documents. It supports advanced configuration through [boost](https://www.mongodb.com/docs/search/query/score/modify-score.md#std-label-scoring-boost expressions like multiply and gaussian decay, as well as analyzers, search operators, and synonyms. To learn more, see [Modify the Score of the Documents in the Results.](https://www.mongodb.com/docs/search/query/score/customize-score.md#std-label-compound-query-custom-score-tutorial
Partial indexes [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search supports partial indexing by using a View with a $match expression. To learn more, see [Example: Filter Documents.](https://www.mongodb.com/docs/search/about/view-support.md#std-label-partially-indexed-collection
Patial match [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search [wildcard](https://www.mongodb.com/docs/search/query/operators-collectors/wildcard.md#std-label-wildcard-ref and [autocomplete](https://www.mongodb.com/docs/search/query/operators-collectors/autocomplete.md#std-label-autocomplete-ref operators support partial match queries.
Single compound index on arrays [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search term indexes are intersected in a single MongoDB Search index and eliminate the need for compound indexes for filtering on arrays.
Synonyms search [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search supports [synonyms](https://www.mongodb.com/docs/search/indexes/synonyms.md#std-label-synonyms-ref defined in a separate collection, which you can reference in your search index for use. To learn more, see the [How to Use Synonyms with MongoDB Search](https://www.mongodb.com/docs/search/tutorial/synonyms-tutorial.md#std-label-synonyms-tutorial tutorial.
Faceting for counts [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search provides fast [counts](https://www.mongodb.com/docs/search/query/counting.md#std-label-count-ref of documents based on text criteria, and also supports [faceted](https://www.mongodb.com/docs/search/query/operators-collectors/facet.md#std-label-fts-facet-ref search for numbers and dates. To learn more, see [How to Use Facets with MongoDB Search.](https://www.mongodb.com/docs/search/tutorial/facet-tutorial.md#std-label-facet-tutorial
Extract metadata [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search facet (MongoDB Search Operator).
Custom analyzers [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search supports [custom analyzers](https://www.mongodb.com/docs/search/indexes/analyzers/custom.md#std-label-custom-analyzers to suit your specific indexing requirements. For example, you can index and search email addresses and HTTP (HyperText Transport Protocol) or HTTPS (Secure HyperText Transport Protocol) URL (Uniform Resource Locator)s using custom analyzers.
Searching phrases or multiple words [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search [phrase](https://www.mongodb.com/docs/search/query/operators-collectors/phrase.md#std-label-phrase-ref operator supports searching for a sequence of terms.
Searching with regular expression [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search provides improved performance when you use the MongoDB Search [autocomplete](https://www.mongodb.com/docs/search/query/operators-collectors/autocomplete.md#std-label-autocomplete-ref operator instead.

See also:

  • [Use $search Instead of $text or $regex](https://www.mongodb.com/docs/search/performance/query-performance.md#std-label-text-to-search - describes how you can replace [$text](https://www.mongodb.com/docs/manual/reference/operator/query/text.md#mongodb-query-op.-text aggregation pipeline stage in your query with [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search to improve both the flexibility and performance of these queries.

  • [Use $search Instead of $text or $regex](https://www.mongodb.com/docs/search/performance/query-performance.md#std-label-regex-to-search - describes how you can replace inefficient regex matching with [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search to improve the performance of text queries.

Learn More

Monitor Performance

You can monitors

Atlas might trigger some Atlas alerts when:

  • MongoDB Search queries your clusters, which can impact Atlas performance metrics, such as the [query targeting](https://www.mongodb.com/docs/atlas/reference/alert-resolutions/query-targeting.md#std-label-query-targeting-resolution metrics.

The [change streams](https://www.mongodb.com/docs/manual/changeStreams.md#std-label-changeStreams cursors that the MongoDB Search process (mongot) uses to keep MongoDB Search indexes updated can contribute to the query targeting ratio and trigger [query targeting alerts](https://www.mongodb.com/docs/atlas/reference/alert-conditions.md#std-label-query-targeting-alerts if the ratio is high.

  • MongoDB Search replicates data from MongoDB, which contributes to the [metrics](https://www.mongodb.com/docs/atlas/monitor-cluster-metrics.md#std-label-monitor-cluster-metrics measured in Atlas, such as the number of getmore operations.

Note:

If your cluster's resources are stretched or near the limits of acceptable performance, consider [upgrading](https://www.mongodb.com/docs/atlas/scale-cluster.md#std-label-scale-cluster to a larger cluster tier before implementing MongoDB Search functionality.

See also:

  • [Storing Source Fields](https://www.mongodb.com/docs/search/performance/index-performance.md#std-label-perf-ref-stored-source

  • [$sort Example](https://www.mongodb.com/docs/search/query/return-stored-source.md#std-label-fts-return-stored-source-egs

Continue Learning

Follow along with this video to learn how to understand, iterate, and improve your MongoDB Search results using [explain](https://www.mongodb.com/docs/search/query/explain.md#std-label-explain-ref and [$search score details.](https://www.mongodb.com/docs/search/query/score/get-details.md#std-label-fts-score-details

Duration: 5 Minutes

Consider Query Operators and Query Complexity

The complexity level of MongoDB Search queries and the type of [operators](https://www.mongodb.com/docs/search/query/operators-collectors/overview.md#std-label-fts-operators used can affect database performance for the node that mongot runs on.

Highly complex queries, such as queries with multiple clauses that use the [compound](https://www.mongodb.com/docs/search/query/operators-collectors/compound.md#std-label-compound-ref operator, or queries which use the [regex](https://www.mongodb.com/docs/search/query/operators-collectors/regex.md#std-label-regex-ref (regular expression) or the [wildcard](https://www.mongodb.com/docs/search/query/operators-collectors/wildcard.md#std-label-wildcard-ref operator, are resource-intensive.

Compound Queries

If your query includes multiple nested [compound](https://www.mongodb.com/docs/search/query/operators-collectors/compound.md#std-label-compound-ref statements, ensure that these are not redundant. If the clauses are added programmatically, consider implementing the logic in the application to avoid inclusion of redundant clauses in the queries. Every score calculation per field that mongot performs, such as for the must and should clauses, increases execution time. To optimize performance, place non-scoring operators such as [equals](https://www.mongodb.com/docs/search/query/operators-collectors/equals.md#std-label-equals-ref, [range](https://www.mongodb.com/docs/search/query/operators-collectors/range.md#std-label-range-ref, and [in](https://www.mongodb.com/docs/search/query/operators-collectors/in.md#std-label-in-ref in the [filter](https://www.mongodb.com/docs/search/query/operators-collectors/compound.md#mongodb-data-filter clause to avoid unnecessary scoring operations.

Faceted Search

You can use the MongoDB Search [facet (MongoDB Search Operator)](https://www.mongodb.com/docs/search/query/operators-collectors/facet.md#std-label-fts-facet-ref collector to extract metadata and avoid running multiple queries for search results and metadata. You can use $search.facet to retrieve both documents and metadata in a single query. If you only need metadata, use $searchMeta.facet to avoid document lookup. For an example, see the [Metadata and Search Results example.](https://www.mongodb.com/docs/search/query/operators-collectors/facet.md#std-label-fts-facet-egs

Use $limit Before $facet

Using a [$limit](https://www.mongodb.com/docs/manual/reference/operator/aggregation/limit.md#mongodb-pipeline-pipe.-limit aggregation pipeline stage after a [$facet](https://www.mongodb.com/docs/manual/reference/operator/aggregation/facet.md#mongodb-pipeline-pipe.-facet aggregation pipeline stage might negatively impact query performance. To avoid performance bottlenecks, use [$limit](https://www.mongodb.com/docs/manual/reference/operator/aggregation/limit.md#mongodb-pipeline-pipe.-limit before [$facet.](https://www.mongodb.com/docs/manual/reference/operator/aggregation/facet.md#mongodb-pipeline-pipe.-facet

Example:

{
  {
    "$search": {...}
  },
  { "$limit": 20 },
  {
    "$facet": {
      "results": [],
      "totalCount": $$SEARCH_META
    }
  }
}

For a demonstration, see the following examples:

  • [Metadata and Search Results Example](https://www.mongodb.com/docs/search/query/operators-collectors/facet.md#std-label-fts-facet-egs

  • [Facet Example](https://www.mongodb.com/docs/search/query/counting.md#std-label-fts-count-aggregation-variable

Minimize Additional MQL Aggregation Stages

Try to encapsulate the entire search logic within the $search stage itself and minimize using additional blocking stages, such as [$group](https://www.mongodb.com/docs/manual/reference/operator/aggregation/group.md#mongodb-pipeline-pipe.-group, [$count](https://www.mongodb.com/docs/manual/reference/operator/aggregation/count.md#mongodb-pipeline-pipe.-count, [$match](https://www.mongodb.com/docs/manual/reference/operator/aggregation/match.md#mongodb-pipeline-pipe.-match, or [$sort](https://www.mongodb.com/docs/manual/reference/operator/aggregation/sort.md#mongodb-pipeline-pipe.-sort. This optimizes the MongoDB Search index usage, and reduces the need for additional database operations in mongod.

Use compound.filter Instead of $match

For queries that require multiple filtering operations, use the [compound Operator](https://www.mongodb.com/docs/search/query/operators-collectors/compound.md#std-label-compound-ref operator with filter clauses. If you must use the [$match](https://www.mongodb.com/docs/manual/reference/operator/aggregation/match.md#mongodb-pipeline-pipe.-match stage in your aggregation pipeline, consider using the [storedSource](https://www.mongodb.com/docs/search/indexes/stored-source-definition.md#std-label-fts-stored-source-definition option to store only the fields that your [$match](https://www.mongodb.com/docs/manual/reference/operator/aggregation/match.md#mongodb-pipeline-pipe.-match condition needs. You can then use the [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search [returnStoredSource](https://www.mongodb.com/docs/search/query/return-stored-source.md#std-label-fts-return-stored-source-option option to retrieve stored fields and avoid the mongod full document lookup.

See also:

  • [Storing Source Fields](https://www.mongodb.com/docs/search/performance/index-performance.md#std-label-perf-ref-stored-source

  • [$match Example](https://www.mongodb.com/docs/search/query/return-stored-source.md#std-label-fts-return-stored-source-egs

Use facet Instead of $group

If you use [$group](https://www.mongodb.com/docs/manual/reference/operator/aggregation/group.md#mongodb-pipeline-pipe.-group to get basic counts for field aggregations, you can use [facet (MongoDB Search Operator)](https://www.mongodb.com/docs/search/query/operators-collectors/facet.md#std-label-fts-facet-ref inside the [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search stage. If you need only metadata results, you can use [facet (MongoDB Search Operator)](https://www.mongodb.com/docs/search/query/operators-collectors/facet.md#std-label-fts-facet-ref inside inside the [$searchMeta](https://www.mongodb.com/docs/search/query/aggregation-stages/searchmeta.md#mongodb-pipeline-pipe.-searchMeta stage instead.

Use count Instead of $count

If you use [$count](https://www.mongodb.com/docs/manual/reference/operator/aggregation/count.md#mongodb-pipeline-pipe.-count to get a count of the number of documents, we recommend that you use [count](https://www.mongodb.com/docs/search/query/counting.md#std-label-count-ref inside the [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search or [$searchMeta](https://www.mongodb.com/docs/search/query/aggregation-stages/searchmeta.md#mongodb-pipeline-pipe.-searchMeta stage instead.

Use sort, near, or returnStoredSource Instead of $sort

  • For sorting numeric, date, string, boolean, UUID, and objectID fields, use the sort option with the [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search stage. To learn more, see [Sort MongoDB Search Results.](https://www.mongodb.com/docs/search/query/sort.md#std-label-sort-ref

  • For sorting geo fields, use the [near](https://www.mongodb.com/docs/search/query/operators-collectors/near.md#std-label-near-ref operator.

  • To sort other fields, use $sort and [returnStoredSource](https://www.mongodb.com/docs/search/query/return-stored-source.md#std-label-fts-return-stored-source-option fields.

Avoid Use of $skip After $search

Using [$skip](https://www.mongodb.com/docs/manual/reference/operator/aggregation/skip.md#mongodb-pipeline-pipe.-skip and [$limit](https://www.mongodb.com/docs/manual/reference/operator/aggregation/limit.md#mongodb-pipeline-pipe.-limit to retrieve results non-sequentially might be slow if the results for your query are large. For optimal performance, use the [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search searchAfter or searchBefore options to paginate results. To learn more, see [Paginate the Results.](https://www.mongodb.com/docs/search/query/paginate-results.md#std-label-fts-paginate-results

To return non-sequential results, such as jumping from page 2 to page 5, you can use the following pipeline stages:

  • [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search searchAfter the last result on Page 2

  • [$skip](https://www.mongodb.com/docs/manual/reference/operator/aggregation/skip.md#mongodb-pipeline-pipe.-skip documents on Pages 3 and 4

  • [$limit](https://www.mongodb.com/docs/manual/reference/operator/aggregation/limit.md#mongodb-pipeline-pipe.-limit results for Page 5

Here, your query is optimized to skip only 2 pages of results, instead of skipping 4 pages if you didn't use searchAfter. For a demonstration of this, see [Paginate the Results.](https://www.mongodb.com/docs/search/query/paginate-results.md#std-label-fts-paginate-results

Use $search Instead of $text or $regex

For applications that rely heavily on MongoDB [$text](https://www.mongodb.com/docs/manual/reference/operator/query/text.md#mongodb-query-op.-text and [$regex](https://www.mongodb.com/docs/manual/reference/operator/query/regex.md#mongodb-query-op.-regex queries, use the following recommendations to determine whether to refactor your applications or migrate your applications to MongoDB Search [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search. The $search aggregation pipeline stage provides features that are either not available through the MongoDB operators or are available through the MongoDB operators but not as performant as MongoDB Search $search.

The following table shows how MongoDB [$regex](https://www.mongodb.com/docs/manual/reference/operator/query/regex.md#mongodb-query-op.-regex, [$text](https://www.mongodb.com/docs/manual/reference/operator/query/text.md#mongodb-query-op.-text, and MongoDB Search [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search address your application's requirements.

If your application requires... Use... Because...
Datastore to respect write concerns [$regex](https://www.mongodb.com/docs/manual/reference/operator/query/regex.md#mongodb-query-op.-regex For transactions with heavy reads after writes, we recommend [$regex](https://www.mongodb.com/docs/manual/reference/operator/query/regex.md#mongodb-query-op.-regex. For [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search, reads after writes should be rare.
Cluster optimized for write performance [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search indexes don't degrade cluster write performance.
Searching through large data sets [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search uses an inverted index, which enables fast document retrieval at very large scales.
Language awareness [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search supports many [language analyzers](https://www.mongodb.com/docs/search/indexes/analyzers/language.md#std-label-ref-language-analyzers that can tokenize (create searchable terms) languages, remove stopwords, and interpret diacritics for improved search relevance.
Case-insensitive text search [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search offers more capabilities than [$regex.](https://www.mongodb.com/docs/manual/reference/operator/query/regex.md#mongodb-query-op.-regex
Highlighting result text [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search [highlighting](https://www.mongodb.com/docs/search/query/highlighting.md#std-label-highlight-ref allows you to contextualize the documents in the results, which is essential for natural language queries.
Geospatial-aware search queries [$regex](https://www.mongodb.com/docs/manual/reference/operator/query/regex.md#mongodb-query-op.-regex or [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB [$regex](https://www.mongodb.com/docs/manual/reference/operator/query/regex.md#mongodb-query-op.-regex and MongoDB Search [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search treat geospatial parameters differently. In MongoDB, lines between coordinates are spherical, which is well-suited for coordinates for long distance such as air flight. MongoDB Search uses Lucene, which draws a straight line between coordinates and is well-suited for short distance.
Autocompletion of search queries [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search For autocomplete.
Fuzzy matching on text input [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search [text](https://www.mongodb.com/docs/search/query/operators-collectors/text.md#std-label-text-ref and [autocomplete](https://www.mongodb.com/docs/search/query/operators-collectors/autocomplete.md#std-label-autocomplete-ref operators support fuzzy matching to filter on input text and address misspelled words (typos).
Filtering based on multiple strings [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search [compound](https://www.mongodb.com/docs/search/query/operators-collectors/compound.md#std-label-compound-ref supports filtering based on multiple strings.
Relevance score sorted search [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search uses the BM25 algorithm for determining the search relevance score of documents. It supports advanced configuration through [boost](https://www.mongodb.com/docs/search/query/score/modify-score.md#std-label-scoring-boost expressions like multiply and gaussian decay, as well as analyzers, search operators, and synonyms. To learn more, see [Modify the Score of the Documents in the Results.](https://www.mongodb.com/docs/search/query/score/customize-score.md#std-label-compound-query-custom-score-tutorial
Partial indexes [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search supports partial indexing by using a View with a $match expression. To learn more, see [Example: Filter Documents.](https://www.mongodb.com/docs/search/about/view-support.md#std-label-partially-indexed-collection
Patial match [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search [wildcard](https://www.mongodb.com/docs/search/query/operators-collectors/wildcard.md#std-label-wildcard-ref and [autocomplete](https://www.mongodb.com/docs/search/query/operators-collectors/autocomplete.md#std-label-autocomplete-ref operators support partial match queries.
Single compound index on arrays [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search term indexes are intersected in a single MongoDB Search index and eliminate the need for compound indexes for filtering on arrays.
Synonyms search [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search supports [synonyms](https://www.mongodb.com/docs/search/indexes/synonyms.md#std-label-synonyms-ref defined in a separate collection, which you can reference in your search index for use. To learn more, see the [How to Use Synonyms with MongoDB Search](https://www.mongodb.com/docs/search/tutorial/synonyms-tutorial.md#std-label-synonyms-tutorial tutorial.
Faceting for counts [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search provides fast [counts](https://www.mongodb.com/docs/search/query/counting.md#std-label-count-ref of documents based on text criteria, and also supports [faceted](https://www.mongodb.com/docs/search/query/operators-collectors/facet.md#std-label-fts-facet-ref search for numbers and dates. To learn more, see [How to Use Facets with MongoDB Search.](https://www.mongodb.com/docs/search/tutorial/facet-tutorial.md#std-label-facet-tutorial
Extract metadata [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search facet (MongoDB Search Operator).
Custom analyzers [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search supports [custom analyzers](https://www.mongodb.com/docs/search/indexes/analyzers/custom.md#std-label-custom-analyzers to suit your specific indexing requirements. For example, you can index and search email addresses and HTTP (HyperText Transport Protocol) or HTTPS (Secure HyperText Transport Protocol) URL (Uniform Resource Locator)s using custom analyzers.
Searching phrases or multiple words [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search [phrase](https://www.mongodb.com/docs/search/query/operators-collectors/phrase.md#std-label-phrase-ref operator supports searching for a sequence of terms.
Searching with regular expression [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search MongoDB Search provides improved performance when you use the MongoDB Search [autocomplete](https://www.mongodb.com/docs/search/query/operators-collectors/autocomplete.md#std-label-autocomplete-ref operator instead.

See also:

  • [Use $search Instead of $text or $regex](https://www.mongodb.com/docs/search/performance/query-performance.md#std-label-text-to-search - describes how you can replace [$text](https://www.mongodb.com/docs/manual/reference/operator/query/text.md#mongodb-query-op.-text aggregation pipeline stage in your query with [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search to improve both the flexibility and performance of these queries.

  • [Use $search Instead of $text or $regex](https://www.mongodb.com/docs/search/performance/query-performance.md#std-label-regex-to-search - describes how you can replace inefficient regex matching with [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-p

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