๐ What is MongoDB?
MongoDB is a NoSQL document-based database that stores data in JSON-like format. Instead of rows and columns, it uses collections and documents. This makes it super flexible and schema-less — perfect for fast-moving modern apps ๐.
SQL = Tables, Rows, Columns ๐
MongoDB = Collections, Documents ๐
❓Why Indexes Matter
Imagine searching a phonebook without alphabetical order — painful, right? ๐ Indexes make your searches faster by letting MongoDB skip scanning every document.
๐ง Types of Indexes in MongoDB
1️⃣ Single Field Index
Most basic and common. You index one field.
db.users.createIndex({ "name": 1 })
1 = ascending, -1 = descending. Used for queries like { name: "Priya" }.
2️⃣ Compound Index
Multiple fields combined to improve multi-field queries.
db.orders.createIndex({ "customerId": 1, "orderDate": -1 })
Order of fields matters! MongoDB can use prefix fields efficiently.
3️⃣ Text Index
Used for searching text phrases in string fields — supports partial matches and relevance scoring.
db.blogs.createIndex({ "content": "text", "title": "text" })
Then query like:
db.blogs.find({ $text: { $search: "MongoDB index" } })
4️⃣ Multikey Index
When field is an array — MongoDB indexes each array element.
db.products.createIndex({ "tags": 1 })
Query example: db.products.find({ tags: "database" })
5️⃣ Hashed Index
Distributes values evenly for sharding or hashed lookups.
db.users.createIndex({ "email": "hashed" })
6️⃣ TTL (Time-To-Live) Index
Auto-deletes documents after a given time — perfect for logs, sessions ⏳.
db.sessions.createIndex({ "createdAt": 1 }, { expireAfterSeconds: 3600 })
7️⃣ Geospatial Index
Used for location-based queries ๐.
db.places.createIndex({ location: "2dsphere" })
8️⃣ Wildcard Index
For dynamic fields when you don’t know which ones to index.
db.dynamic.createIndex({ "$**": 1 })
9️⃣ Unique Index
Ensures values are not duplicated.
db.users.createIndex({ "email": 1 }, { unique: true })
๐ Partial / Sparse Index
Indexes only documents meeting a condition (saves space!).
db.users.createIndex({ age: 1 }, { partialFilterExpression: { age: { $gte: 18 } } })
๐ Quick Comparison Table
| Index Type | Use Case | Example |
|---|---|---|
| Single | One field | { name: 1 } |
| Compound | Multi-field queries | { age:1, city:1 } |
| Text | Text search | { title:"text" } |
| Hashed | Sharding / random lookup | { id:"hashed" } |
| TTL | Auto delete | { createdAt:1 } |
๐ฏ Real Example — Speed Boost!
Query before index:
db.users.find({ name: "Priya" })
Took 2.3 sec ⏳
After index:
db.users.createIndex({ name: 1 })
Took 0.02 sec ⚡
๐ฃ️ Interview Quickfire Q&A
- ๐ฌ Q: What’s the default index in MongoDB?
A: The_idfield — automatically indexed! - ๐ฌ Q: How is text index different from search index?
A: Text index = keyword search. Search index (Atlas Search) = full Lucene-based search engine with scoring. - ๐ฌ Q: Can we have multiple text indexes per collection?
A: Nope ❌ Only one text index allowed per collection.
๐ Conclusion
Indexes are the superpower of MongoDB ⚙️ — they turn slow lookups into lightning-fast queries ⚡. But use wisely: too many indexes = slower writes.
db.collection.explain("executionStats") to see if an index is actually used.
๐ Keep learning, keep indexing smart! ๐
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