What Is a TTL Expiration Indexes in MongoDB?
A single-field date index lets a background process delete documents after expiration. Cleanup is asynchronous, not an exact timer.
How the TTL Expiration Indexes Algorithm Works
A single-field date index lets a background process delete documents after expiration. Cleanup is asynchronous, not an exact timer.
When to Use TTL Expiration Indexes
Sessions, temporary cache records, or whole documents with a retention deadline.
How to Create a MongoDB TTL Expiration Indexes
Review data quality, existing structures, feature support, build time, and deployment requirements before creating an index on a production table.
db.sessions.createIndex({ expiresAt: 1 }, { expireAfterSeconds: 0 })TTL Expiration Indexes Query Example
This example demonstrates the matching query shape. Check the execution plan to confirm that the engine can use the index.
db.sessions.find({ expiresAt: { $gt: new Date() } })Queries Supported by TTL Expiration Indexes
Sessions, temporary cache records, or whole documents with a retention deadline. A similar-looking predicate may not use the same access path; operators, expressions, key order, and data type all matter.
Read Performance, Storage, and Write Costs
Deletion creates write and replication work; TTL removes a document, not individual fields. Indexes reduce some search work but require storage and add maintenance to writes.
TTL Expiration Indexes Limitations and Common Mistakes
Use a date field and single-field index. Do not rely on deletion at an exact second.
Do not assume that an index being present means the optimizer chose it or that the query became selective.
How to Measure and Tune TTL Expiration Indexes
Monitor expiration lag; store an explicit per-document expiry when lifetimes differ.
Compare representative plans and timings before and after, including concurrent writes and realistic data volumes.
TTL Expiration Indexes Questions
Will the database always use this index?
No. The optimizer weighs selectivity, estimated costs, statistics, cache state, and the amount of data returned.
What should I verify before production?
Confirm version support, query compatibility, write overhead, build/rollback procedures, and index behavior during backup and recovery.
Official MongoDB Index Documentation
Check MongoDB documentation: Index Types for release-specific requirements and supported operators.