MongoDB - Interview Questions and Answers
MongoDB is a NoSQL database that stores data in a flexible, JSON-like format (BSON). It is schema-less and supports horizontal scaling.
BSON (Binary JSON) is MongoDB?s format for storing data, supporting additional types like Date and ObjectId.
Simply switch to a database name
use myDatabaseThe database is created when you insert data.
MongoDB creates collections dynamically when inserting documents:
db.createCollection("users")
db.users.insertOne({ name: "Alice" })
se insertOne() or insertMany()
db.users.insertOne({ name: "Alice", age: 25 })
db.users.insertMany([{ name: "Bob" }, { name: "Charlie" }])
db.users.find()
Use a query inside find()
db.users.find({ age: 25 })
Use projection:
db.users.find({}, { name: 1, _id: 0 })
db.users.find().sort({ age: -1 }) // Sort by age descending
db.users.find().limit(5)
db.users.updateOne({ name: "Alice" }, { $set: { age: 26 } })
db.users.updateMany({}, { $set: { status: "active" } })
db.users.updateOne({ name: "Alice" }, { $inc: { age: 1 } })
db.users.updateMany({}, { $rename: { "oldField": "newField" } })
db.users.replaceOne({ name: "Alice" }, { name: "Alice", age: 30, city: "NY" })
db.users.deleteOne({ name: "Alice" })
db.users.deleteMany({ age: { $lt: 18 } })
db.users.drop()
db.dropDatabase()
deleteOne() removes the first matching document, while remove() can remove multiple.
An index improves query performance by speeding up searches.
db.users.createIndex({ name: 1 }) // Ascending index
db.users.createIndex({ email: 1 }, { unique: true })
db.users.getIndexes()
db.users.dropIndex("name_1")
Aggregation processes data and returns computed results, like GROUP BY in SQL.
db.users.aggregate([
{ $match: { age: { $gt: 20 } } },
{ $group: { _id: "$city", total: { $sum: 1 } } }
])
Filters documents (like WHERE in SQL).
Groups data based on a field.
Selects which fields to include in the output.
Use $lookup:
db.orders.aggregate([
{ $lookup: { from: "users", localField: "userId", foreignField: "_id", as: "userDetails" } }
])
Embedding stores data inside the document, referencing stores IDs.
When data is frequently read together.
When data is large and frequently updated.
Use arrays or references.
Yes, since version 4.0.
const session = db.getMongo().startSession();
session.startTransaction();
Use transactions, write concerns, and validation rules.
db.createUser({ user: "admin", pwd: "password", roles: ["readWrite"] })
Use --auth when starting MongoDB
Replication keeps multiple copies of data for high availability.
A group of MongoDB servers with primary and secondary nodes.
Sharding distributes data across multiple machines.
When the dataset is too large for a single server.
rs.status()
A cloud database service for MongoDB.
A fixed-size collection that overwrites old data.
mongodump --db myDatabase
mongorestore --db myDatabase dump/
A MongoDB feature for storing large files.
Tutorials
Random Blogs
- AI Agents & Autonomous Systems – The Future of Self-Driven Intelligence
- What Is SEO and Why Is It Important?
- Important Mistakes to Avoid While Advertising on Facebook
- Role of Digital Marketing Services to Uplift Online business of Company and Beat Its Competitors
- Best Platform to Learn Digital Marketing in Free
- String Operations in Python
- Understanding AI, ML, Data Science, and More: A Beginner's Guide to Choosing Your Career Path
- Generative AI - The Future of Artificial Intelligence
- 5 Ways Use Jupyter Notebook Online Free of Cost
- Downlaod Youtube Video in Any Format Using Python Pytube Library
