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. How to structure your answer (60–90 seconds) Define SQL queries in plain languag…
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. How to structure your answer (60–90 seconds) Define Schema design in plain langu…
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. How to structure your answer (60–90 seconds) Define Transactions in plain langua…
Mid Detailed
Compare two approaches to Indexing—when would you choose each?
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. How to structure your answer (60–90 seconds) Define Indexing in plain language f…
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. How to structure your answer (60–90 seconds) Define Normalization in plain langu…
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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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