Learn how MongoDB indexes speed up queries. This tutorial walks through creating single field, compound, TTL, and covered query indexes with Node.js examples.

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A hands-on tutorial covering MongoDB index types and their impact on query performance using Node.js and MongoDB Atlas. It walks through provisioning an Atlas cluster via CLI, loading sample data, and running queries with explain plans to compare COLLSCAN vs IXSCAN. Covers single-field indexes, compound indexes, covered queries (where Total Docs Examined drops to 0), and TTL indexes for auto-expiring documents. Includes a linear vs binary search simulation to illustrate why indexes work, plus practical guidance on write overhead trade-offs and index sizing.

MongoDB Indexes: Improve Query Performance with Node.js

Step 3 — Simulating Linear vs. Binary Search

Step 4 — Querying with a COLLSCAN (No Index)

Step 5 — Querying with a Single Field Index

Step 6 — Querying with a Compound Index (Optimized)

Step 8 — Managing Data with TTL Indexes