Lesson 46/100

Tutorials MongoDB Tutorial

TTL Indexes

TTL Indexes: free step-by-step lesson with examples, common mistakes, and interview tips — part of MongoDB Tutorial on Toolliyo Academy.

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MongoDB Tutorial · Lesson 46 of 100

TTL Indexes

Foundations & CRUD ✓Queries & SchemaAggregation & ScaleAtlas & Projects

Queries & Schema · 2 — Design · ~6 min · MongoDB — Indexing & Performance

What is this?

A TTL (time-to-live) index deletes documents automatically after a delay based on a date field. MongoDB’s background thread removes expired docs.

Why should you care?

Sessions, OTPs, password-reset tokens, and temporary uploads should disappear without a custom cron at first.

See it live — copy this example

Open mongosh or MongoDB Compass, select database nosqlverse, then run the example. Change one field and run again.

db.sessions.insertOne({
  userId: ObjectId(),
  token: "abc",
  createdAt: new Date()
})
db.sessions.createIndex({ createdAt: 1 }, { expireAfterSeconds: 3600 })
db.sessions.find()

Run Example »

Edit the code below and click Run to see the result in Toolliyo’s live editor.

Code
Result

What happened?

  • createdAt is a real Date.
  • The TTL index expires documents 3600 seconds after createdAt.
  • The delete is not instant to the second — a background job runs periodically.

Practice next

  1. Create sessions with createdAt: new Date().
  2. Create TTL index with a short expireAfterSeconds (e.g. 60) for a test.
  3. Wait and confirm documents disappear.
  4. Use expireAfterSeconds: 0 with a absolute expireAt date field pattern.
  5. Partial filter TTL only for type: "otp".

Remember

TTL indexes auto-delete old documents. Need a BSON date field. Perfect for sessions and OTPs.

OTP collection cleanup

Login OTPs expire in 5 minutes via TTL on createdAt.

Outcome: No leftover codes clutter the database.

Interview prep for this lesson

Practice these questions aloud after reading—each links to a full structured answer.

Junior Detailed
Explain SQL queries in the context of MongoDB.
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define SQL queri…
Mid Detailed
What are common mistakes teams make with Schema design when using MongoDB?
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define Schema de…
Senior Detailed
How would you debug a production issue related to Transactions in a MongoDB application?
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define Transacti…
Junior Detailed
Describe a real-world scenario where Normalization mattered in a MongoDB project.
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define Normaliza…
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MongoDB Tutorial
Course syllabus

MongoDB Tutorial

MongoDB — Foundations
MongoDB — CRUD Operations
MongoDB — Query Operators
MongoDB — Schema Design
MongoDB — Indexing & Performance
MongoDB — Aggregation Pipelines
MongoDB — Replication & Sharding
MongoDB — Atlas & Security
MongoDB — Modern Features
MongoDB — Real-World Projects
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