Indexes deep dive in MongoDB

What are Indexes in MongoDB ? Indexes are used to improve the speed of queries . Without index → MongoDB scans every document (slow) With index → MongoDB quickly finds data (fast) Think of it like: Index in a book → helps you find topics quickly instead of reading every page 🔹 Why Indexes are Important Faster data retrieval Efficient searching Improves performance for large datasets 🔹 How Index Works MongoDB creates a data structure (like a sorted list) Example: If you index age , MongoDB stores sorted values → 20, 25, 30, 35 So searching becomes very fast 🔹 Create an Index db.users.createIndex({ age: 1 }) 1 → ascending -1 → descending 🔹 Types of Indexes 1. Single Field Index Index on one field db.users.createIndex({ age: 1 }) 2. Compound Index Index on multiple fields db.users.createIndex({ age: 1, name: 1 }) Used when queries involve multiple fields 3. Unique Index Ensures values are unique db.users.createIndex({ email: 1 }, { unique: true }) Prevents duplicate values 4. Text Index Used for searching text db.users.createIndex({ name: "text" }) Useful for search features 5. Multikey Index Used for arrays Automatically created when indexing array fields 🔹 Default Index MongoDB automatically creates an index on: _id (ObjectId) Ensures every document is unique 🔹 Check Indexes db.users.getIndexes() 🔹 Drop Index db.users.dropIndex({ age: 1 }) 🔹 When to Use Indexes Use indexes when: You frequently search a field You use sorting You filter large data Avoid too many indexes because: They take memory Slow down insert/update Simple Understanding Index = speed booster More indexes = faster reads but slower writes  🔹 What are Special Indexes? Special indexes are advanced indexes designed for specific use cases , beyond normal single or compound indexes. 🔹 1. Text Index Used for searching text content Example: db.posts.createIndex({ title: "text", content: "text" })  Supports keyword search like: search articles search products  Used in: blogs, search features 🔹 2. Geospatial Index Used for location-based queries Types: 2d → flat coordinates 2dsphere → real-world earth coordinates Example: Find nearby restaurants Delivery apps 🔹 3. TTL Index (Time-To-Live) Automatically deletes documents after a certain time Example: db.sessions.createIndex({ createdAt: 1 }, { expireAfterSeconds: 3600 }) Document will be deleted after 1 hour Used in: session data cache data 🔹 4. Sparse Index Indexes only documents that contain the field Example: db.users.createIndex({ email: 1 }, { sparse: true }) Documents without email are ignored 🔹 5. Partial Index Indexes only documents that match a condition Example: db.users.createIndex( { age: 1 }, { partialFilterExpression: { age: { $gt: 18 } } } ) Only users with age > 18 are indexed 🔹 6. Hashed Index Used for sharding and equal distribution Example: db.users.createIndex({ userId: "hashed" })  Good for: distributed systems balancing load 🔹 7. Wildcard Index Indexes all fields or dynamic fields Example: db.products.createIndex({ "$**": 1 })  Useful when schema is flexible Simple Understanding Text → search words Geo → location queries TTL → auto delete Sparse → ignore missing fields Partial → filter-based index Hashed → distribution Wildcard → dynamic fields