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Analyze Query Performance

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Identify Slow Queries

Performance Overview
Analyze a Slow Query
Perform Advanced Query Analysis

MongoDB provides several ways to examine the performance of your workload, allowing you to understand query performance and identify long-running queries. Understanding query performance helps you build effective indexes and ensure your application runs critical queries efficiently.

Identify Slow Queries

Use the following methods to identify slow queries that occur on your deployment.

Performance Overview

The following methods provide overviews of your deployment's performance. Use these methods to determine if there are performance issues that need to be addressed:

Method	Availability	Description
Use the Atlas Performance Advisor	M10+ Atlas clusters	The Atlas Performance Advisor monitors slow queries and suggests new indexes to improve performance. For more information, see Monitor and Improve Slow Queries.
Check ongoing operations in Atlas	M10+ Atlas clusters	You can use the Atlas Real-Time Performance Panel (RTPP) to see current network traffic, database operations, and hardware statistics.
Check ongoing operations locally	Atlas clusters and self-hosted deployments	The `$currentOp` aggregation stage returns information on active operations and cursors. Use `$currentOp` to identify long-running or stuck operations that may be negatively impacting performance. You can also use the `top` command to get additional operation count and latency statistics..
Check server metrics	Atlas clusters and self-hosted deployments	For Atlas clusters, you can view cluster metrics to identify performance issues. For self-hosted deployments, the `serverStatus` command provides metrics that can indicate poor performance and anomalies for query execution.
View index statistics	Atlas clusters and self-hosted deployments	The `$indexStats` aggregation stage returns information about your collection's indexes and how often individual indexes are used. Use `$indexStats` to identify unused indexes that can be removed to improve write performance.

Analyze a Slow Query

Use these methods to analyze a slow query and determine the cause of poor performance:

Method	Availability	Description
Use the Atlas Query Profiler	M10+ Atlas clusters	The Atlas Query Profiler shows long-running operations and performance statistics. For more information, see Monitor Query Performance.
Enable the Database Profiler	Atlas clusters and self-hosted deployments	When enabled, the database profiler stores information about slow queries in the `system.profile` collection. For more information, see Database Profiler.
View slow queries in the diagnostic log	Atlas clusters and self-hosted deployments	MongoDB logs queries that exceed the slow operation threshold (default 100 milliseconds) in the diagnostic logs. Check the diagnostic logs to identify problematic queries and see which queries would benefit from indexes.
View explain results	Atlas clusters and self-hosted deployments	Query explain results show information on the query plan and execution statistics. You can use explain results to determine the following information about a query: The amount of time a query took to execute Whether the query used an index The number of documents and index keys scanned to fulfill a query To view explain results, use the following methods: `db.collection.explain()` `explain()` cursor method To learn about explain results output, see Explain Results and Interpret Explain Plan Results.

Perform Advanced Query Analysis

The following methods are suited for deeper investigation of problematic queries, and can provide fine-grained performance insights:

Method	Availability	Description
View plan cache statistics	Atlas clusters and self-hosted deployments	The `$planCacheStats` aggregation stage returns information about a collection's plan cache. The plan cache contains query plans that the query planner uses to efficiently complete queries. Generally, the plan cache should contain entries for your most commonly-run queries.

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