Complete Guide to MongoDB Indexing for High-Performance Queries

MongoDB is a powerful NoSQL database, but performance can drastically suffer without proper indexing. In this guide, we’ll explore how to use indexes in MongoDB to improve query speed, optimize reads, and maintain application scalability. Whether you're building a production app or optimizing an existing database, these strategies will help you get the most out of your MongoDB setup.

Table of Contents

1. What is Indexing in MongoDB?

2. Single Field Index

3. Compound Index

4. TTL Index (Time-To-Live)

5. Partial Index

6. Using Explain Plans

7. Best Practices and Real-World Scenarios

8. Conclusion

1. What is Indexing in MongoDB?

Indexes support the efficient execution of queries in MongoDB. Without indexes, MongoDB must perform a collection scan, i.e., scan every document in a collection to select those documents that match the query statement.

2. Single Field Index

The most basic type of index is a single field index. It's created on a single field to improve performance for queries filtering or sorting on that field.

Example:

db.users.createIndex({ age: 1 })

3. Compound Index

Compound indexes are created on multiple fields. They're useful when queries filter or sort on multiple fields in the index order.

Example:

db.orders.createIndex({ userId: 1, createdAt: -1 })

4. TTL Index (Time-To-Live)

TTL indexes automatically remove documents after a certain time. Useful for sessions, temporary logs, etc.

Example:

db.sessions.createIndex({ "createdAt": 1 }, { expireAfterSeconds: 3600 })

5. Partial Index

Partial indexes index only the documents that meet a specified filter expression. They reduce index size and improve write performance.

Example:

db.users.createIndex({ email: 1 }, { partialFilterExpression: { email: { $exists: true } } })

6. Using Explain Plans

MongoDB's explain plans show how queries are executed. Use them to diagnose slow queries and ensure indexes are used.

Example:

db.users.find({ age: 30 }).explain('executionStats')

7. Best Practices and Real-World Scenarios

- Always create indexes based on your query patterns.
- Use compound indexes over multiple single indexes.
- Monitor performance using explain plans.
- Be cautious with write-heavy workloads; indexes can impact write speed.
- Periodically review and drop unused indexes using db.collection.getIndexes().

8. Conclusion

Indexing is one of the most powerful performance tools in MongoDB. With the right indexing strategy, you can drastically speed up queries and reduce server load. Make indexing a core part of your database design process.