Atlas Performance Advisor index suggestions
Parent: MongoDB Explain Plans, Query Planner and Plan Cache · Published reference · snapshot 2026-10-20 · skill ranked-e3681427
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Source-anchored research for Atlas Performance Advisor index suggestions. Run status: COMPLETED.
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Problems, failure modes and limitations
- Atlas Performance Advisor groups operations it considers slow into common query shapes and suggests indexes for those observed patterns. (high confidence) (verified as of 2026-10-20) [source]
- MongoDB currently documents that the Advisor provides no performance suggestions for time-series collections and cannot suggest indexes for databases using the ctime timestamp format. (low confidence) (verified as of 2026-10-20) [source]
- Atlas Performance Advisor is available on M10+ clusters. It monitors operations Atlas classifies as slow, groups affected queries by query shape, and presents sample queries and metrics such as execution count, average execution time, documents scanned and returned, and average object size. (high confidence) (verified as of 2026-10-20) [source]
- MongoDB's current Atlas documentation says Performance Advisor does not provide suggestions for time-series collections, cannot suggest indexes for the ctime timestamp format, and may pause collecting new logs temporarily during extreme log-volume spikes. (low confidence) (verified as of 2026-10-20) [source]
Comparisons and alternatives
- Before creating a suggested index, compare it with existing indexes and query frequency; MongoDB warns that extra indexes consume storage and add write work, and independent guides describe the same tradeoff. (high confidence) [source]
- A study submitted on 2024-09-25 found that MongoDB 7.0.1's First Past the Post query optimizer sometimes preferred an index scan when a collection scan ran faster, and could select plans taking more than twice the optimal runtime. The study did not evaluate Atlas Performance Advisor; it supports measuring a suggested change against the target query rather than assuming an added index must improve runtime. (medium confidence) (verified as of 2024-09-25) [source]
Facts and statements
- For each suggested index, the Advisor shows affected query metrics and sample query shapes; documented metrics include execution count, average execution time, documents scanned and returned, object size, and in-memory sorts. (medium confidence) (verified as of 2026-10-20) [source]
- MongoDB ranks suggested indexes by Impact, an estimate of performance improvement based on total wasted bytes read. Its ranking documentation says the calculation considers query execution time, documents scanned and returned, and average object size. (high confidence) (verified as of 2026-10-14) [source]
- One r/mongodb user said they initially followed Atlas suggestions blindly and later reconsidered a growing index set on a central collection; this is one workload report and does not establish that the Advisor generally over-recommends. (low confidence) [source]
- The Atlas index-ranking documentation says it does not suggest indexes with more than 16 fields and requires the difference between documents scanned and returned to exceed 500 for impacted queries. (medium confidence) (verified as of 2026-10-14) [source]
- Impact describes an estimated benefit, not a measured post-build result. Atlas advises considering how often the affected query runs and the collection's read/write mix; OneUptime's guide also recommends checking index overlap and measuring query execution after creation. Treat the rank as a prioritization signal and verify the candidate against the target workload. (medium confidence) [source]
- Before creating a suggested read index, compare it with existing indexes and weigh affected-query benefit against write and storage costs. Atlas says indexes must be maintained during writes; Percona warns that too many indexes can hurt write performance and optimizer efficiency and waste disk and RAM. (medium confidence) [source]
Children
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