MongoDB Top 25 Most Asked Interview Questions and Answers

Are you preparing for a MongoDB interview in 2025? Whether you’re a fresher or an experienced developer, this guide features MongoDB Top 25 Most Asked Interview Questions and Answers, combined with definitions, real-life examples, and clear explanations. From documents, collections, and indexing to replica sets and sharding, this post highlights the Top Interview Questions you’re most likely to face and will help you gain confidence to crack your next technical round.

1. What is MongoDB and why is it called a NoSQL database?

Definition: MongoDB is an open-source, document-oriented NoSQL database designed to store, manage, and retrieve large volumes of unstructured or semi-structured data using a flexible, JSON-like format called BSON (Binary JSON).

🧠 Why is MongoDB Called a NoSQL Database?

The term NoSQL means “Not Only SQL.” MongoDB falls under this category because:

• It does not use traditional relational tables with rows and columns.
  
  
• It doesn’t require a fixed schema, making it highly flexible.
  
  
• It stores data in documents, not in relational tables.
  
  
• It is designed for horizontal scalability, distributed data, and high performance.
  
  

Example:

{ “_id”: 1, “name”: “Alice”, “age”: 25, “skills”: [“Python”, “AI”] }

2. What is a Document in MongoDB?

Definition: In MongoDB, a document is a basic unit of data that is stored in a collection. It is similar to a row in a relational database but far more flexible. Documents are stored in BSON (Binary JSON) format and can contain nested fields, arrays, and even other documents.

🧠 Key Characteristics:

• Schema-less: Each document can have a different structure.
  
  
• Hierarchical/Nested: Can store arrays and embedded documents.
  
  
• Human-readable format (JSON) but stored in efficient binary format (BSON).
  
  
• Every document has a unique _id field that acts like a primary key.

Example:

{

  “_id”: ObjectId(“64fe90cde342b2f5d91f87b1”),

  “name”: “Alice”,

  “age”: 25,

  “email”: “alice@example.com”,

  “skills”: [“Python”, “Data Analysis”, “Machine Learning”],

  “address”: {

    “city”: “Delhi”,

    “zip”: “110001”

  }

}

3. What is a Collection in MongoDB?

Definition: In MongoDB, a collection is a group of MongoDB documents, similar to a table in relational databases. Collections store related documents together and do not enforce a schema, meaning each document in a collection can have a different structure.

🧠 Key Features of a Collection:

• Schema-less: Documents in the same collection can have different fields and data types.
  
  
• Grouped storage: Used to logically organize related data (e.g., users, orders, products).
  
  
• Stored in databases (MongoDB has databases → collections → documents).
  
  
• Automatically created when you insert the first document if it doesn’t exist.

Example: A collection called users may hold multiple documents like:

// Document 1

{

  “name”: “Alice”,

  “email”: “alice@example.com”

}

// Document 2

{

  “name”: “Bob”,

  “email”: “bob@example.com”,

  “age”: 30,

  “address”: { “city”: “Mumbai”, “zip”: “400001” }

}

4. What is BSON?

Definition: BSON (Binary JSON) is a binary-encoded serialization format used by MongoDB to store documents in a more efficient, faster, and type-rich way than plain JSON. It stands for Binary JavaScript Object Notation.

🔍 Key Features of BSON:

5. What are the advantages of MongoDB over RDBMS?

6. What is the _id field in MongoDB?

Definition: In MongoDB, the _id field is a unique identifier for each document in a collection. It acts like the primary key in relational databases.

🔍 Definition:

• Every document must have an _id field.
  
  

• • If you don’t provide one, MongoDB automatically generates an ObjectId value for it.
    
    

• The _id field is immutable—once set, it cannot be changed.

Example:

{

  “_id”: ObjectId(“64e25f59c1b59b6e6e8a5c19”),

  “name”: “John Doe”,

  “email”: “john@example.com”

}

7. How to insert a document into MongoDB?

Definition: In MongoDB, documents are inserted into collections using the insertOne() or insertMany() method. Documents must follow BSON format (similar to JSON) and must include or be automatically assigned a unique _id.

1. 
   Using insertOne()

This method is used to insert a single document into a collection.

db.collection_name.insertOne({ key1: value1, key2: value2, … })

🧪 Example:

db.users.insertOne({

  name: “Alice”,

  age: 28,

  email: “alice@example.com”

})

2. Using insertMany()

This method is used to insert multiple documents at once.

📌 Syntax:

db.collection_name.insertMany([

  { key1: value1, key2: value2 },

  { key1: value1, key2: value2 }

])

🧪 Example:

db.products.insertMany([

  { name: “Laptop”, price: 800 },

  { name: “Phone”, price: 500 }

])

8. What is the difference between insertOne() and insertMany()?

1. Using insertOne()

This method is used to insert a single document into a collection.

db.collection_name.insertOne({ key1: value1, key2: value2, … })

🧪 Example:

db.users.insertOne({

  name: “Alice”,

  age: 28,

  email: “alice@example.com”

})

2. Using insertMany()

This method is used to insert multiple documents at once.

📌 Syntax:

db.collection_name.insertMany([

  { key1: value1, key2: value2 },

  { key1: value1, key2: value2 }

])

🧪 Example:

db.products.insertMany([

  { name: “Laptop”, price: 800 },

  { name: “Phone”, price: 500 }

])

9. How do you query documents in MongoDB?

MongoDB uses the find() and findOne() methods to query documents from a collection. These queries use JSON-like syntax to match documents based on specific criteria.

1. Using find() Method

Returns a cursor to all matching documents.

db.collection_name.find({ query })

db.users.find({ age: 25 })

🔍 Returns all users whose age is 25.

2. Using findOne() Method

Returns only the first matching document.

🧪 Example:

db.users.findOne({ name: “Alice” })

🧾 Returns the first document where name is “Alice”.

db.students.find({ age: { $gt: 20 } });

10. What are MongoDB indexes?

Definition: Indexes in MongoDB are special data structures that improve the speed and efficiency of query operations on a collection, much like indexes in relational databases. Without indexes, MongoDB must scan every document in a collection to find matches (called a collection scan), which can be slow for large datasets.

Why Use Indexes?

• Boost query performance
  
  
• Reduce response time
  
  
• Avoid full collection scans
  
  
• Allow efficient sorting and range queries

Example:

db.users.find({ _id: ObjectId(“abc123”) })

This uses the default index on _id.

11. What is aggregation in MongoDB?

Definition: Aggregation in MongoDB is a powerful framework used to process data records and return computed results. It performs operations like filtering, grouping, sorting, reshaping, and transforming data — similar to SQL’s GROUP BY, SUM, AVG, and JOIN operations.

Example:

db.sales.aggregate([

  { $group: { _id: “$item”, total: { $sum: “$amount” } } }

]);

🔑 Core Stages in Aggregation Pipeline:

12. What is the difference between find() and findOne()?

In MongoDB, both find() and findOne() are used to query documents from a collection — but they serve different purposes and return different types of results.

🔍 find() – Returns a Cursor (Multiple Documents)

• The find() method retrieves all documents that match the query criteria.
  
  
• It returns a cursor, which can be iterated to access each matching document.
  
  
• You can use .toArray(), .limit(), .sort() etc. on the result.
  
  

Syntax:

db.collection.find({ field: value })

Example:

db.users.find({ age: { $gte: 25 } })

📌 Returns:

[

  { _id: 1, name: “Alice”, age: 25 },

  { _id: 2, name: “Bob”, age: 30 }

]

🔎 findOne() – Returns a Single Document

• The findOne() method returns only the first matching document.
  
  
• It does not return a cursor; it returns the document directly or null if no match is found.
  
  

Syntax:

db.collection.findOne({ field: value })

Example:

db.users.findOne({ age: { $gte: 25 } })

📌 Returns:

{ _id: 1, name: “Alice”, age: 25 }

Even if multiple documents match, only one is returned — not guaranteed to be the same order unless you sort explicitly.

13. What is a replica set in MongoDB?

Definition: A Replica Set in MongoDB is a group of mongod instances (MongoDB servers) that maintain the same data set to provide high availability and data redundancy.

It is MongoDB’s way of implementing replication — a key feature for fault tolerance and disaster recovery.

💻 MongoDB Command to Initiate a Replica Set (local development)

rs.initiate({

  _id: “rs0”,

  members: [

    { _id: 0, host: “localhost:27017” },

    { _id: 1, host: “localhost:27018” },

    { _id: 2, host: “localhost:27019” }

  ]

})

🔄 How It Works

1. Primary Node:
   
   
   • Only one in the replica set.
     
     
   • Handles all write operations.
     
     
   • Reads can also go here (by default).
     
     
2. Secondary Nodes:
   
   
   • Replicate data asynchronously from the primary.
     
     
   • If the primary goes down, automatic failover occurs and one of the secondaries becomes the new primary.
     
     
3. Arbiter Node (optional):
   
   
   • Participates in elections but doesn’t store data.
     
     
   • Helps in maintaining an odd number of votes for failover quorum.
     
     

🔧 Example Replica Set Structure

replicaSet: rs0

  Primary        Secondary        Secondary

    |                |                |

  [Node A]  <—-  [Node B]  <—-  [Node C]

    |

    ↓

 Accepts Write Operations

14. What is sharding in MongoDB?

Definition: Sharding is the process of splitting and distributing data across multiple servers or clusters (called shards) in MongoDB to handle large datasets and ensure horizontal scalability.

MongoDB uses sharding to support deployment of very large data sets and high throughput operations.

⚙️ How Sharding Works

• Shard: Each shard contains a subset of the data. It is a MongoDB instance (or replica set) that stores actual data.
  
  
• mongos: It acts as a query router, directing client requests to the correct shard.
  
  
• Config Servers: Store metadata and configuration about the cluster and data distribution.

15. What is MongoDB Compass?

Definition: MongoDB Compass is the official GUI (Graphical User Interface) for MongoDB, developed by MongoDB Inc. It provides a visual environment to explore, manage, and analyze MongoDB data without writing code.

💡 Key Features of MongoDB Compass

16. Explain the update operations in MongoDB.

MongoDB provides powerful update operations to modify documents in a collection. You can update a single document, multiple documents, or even upsert (update or insert if not found).

1. updateOne()

Updates a single document that matches the specified filter.

db.users.updateOne(

   { name: “Alice” },

   { $set: { age: 30 } }

)

Updates the age field of the first user named Alice to 30.

2. updateMany()

Updates all documents that match the filter condition.

db.users.updateMany(

   { isActive: true },

   { $set: { lastLogin: new Date() } }

)

Sets lastLogin timestamp for all active users.

17. What is upsert in MongoDB?

Definition: An operation that updates a document if it exists, inserts it otherwise.

Example:

db.users.updateOne({ name: “Lily” }, { $set: { age: 30 } }, { upsert: true });

18. What is the difference between $set and $push?

In MongoDB, both $set and $push are update operators, but they serve different purposes and act on different types of data.

$set – Used to Update or Add a Field with a Specific Value

• It assigns a value to a field, whether the field exists or not.
  
  
• If the field does not exist, $set will create it.
  
  
• If the field does exist, $set will overwrite its value.
  
  

Syntax:

db.collection.updateOne(

  { _id: 1 },

  { $set: { name: “Alice”, age: 25 } }

)

📌 Example Before:

{ _id: 1, name: “Bob” }

📌 After $set:

{ _id: 1, name: “Alice”, age: 25 }

$push – Used to Add a Value to an Array Field

• It appends a value to an existing array field.
  
  
• If the array field doesn’t exist, MongoDB will create it as an array and then insert the value.
  
  

Syntax:

db.collection.updateOne(

  { _id: 1 },

  { $push: { skills: “Python” } }

)

📌 Example Before:

{ _id: 1, name: “Alice”, skills: [“JavaScript”] }

📌 After $push:

{ _id: 1, name: “Alice”, skills: [“JavaScript”, “Python”] }

19. What is the use of $in operator?

The $in operator in MongoDB is used to match values within an array of specified values. It’s similar to the SQL IN clause and helps you query documents where a field’s value matches any one of the values in a given array.

📘 Example

Suppose you have a products collection:

{

  “_id”: 1,

  “name”: “Laptop”,

  “category”: “Electronics”

},

{

  “_id”: 2,

  “name”: “Toothpaste”,

  “category”: “Health”

},

{

  “_id”: 3,

  “name”: “Smartphone”,

  “category”: “Electronics”

}

You can find all products in the “Electronics” or “Health” category using:

db.products.find({

  category: { $in: [“Electronics”, “Health”] }

})

This will return both the Laptop, Toothpaste, and Smartphone documents.

20. What is a capped collection?

Definition: A capped collection in MongoDB is a fixed-size, circular collection that maintains the insertion order of documents and automatically overwrites the oldest documents when the specified size limit is reached.

Key Characteristics

21. What is GridFS in MongoDB?

Definition: GridFS is a specification in MongoDB used to store and retrieve large files, such as images, videos, audio, PDFs, or any binary data that exceeds the BSON-document size limit of 16 MB.

Instead of storing a file in a single document, GridFS splits the file into smaller chunks (default: 255 KB each) and stores each chunk as a separate document in a collection.

Why Use GridFS?

MongoDB’s documents are limited to 16 MB in size. When files exceed this limit:

• You can’t store them directly in a single document.
  
  
• GridFS solves this by chunking the file and storing metadata.
  
  

How GridFS Works

GridFS uses two collections:

Each chunk is stored with:

• files_id: Reference to the file in fs.files
  
  
• n: Sequence number of the chunk
  
  
• data: The binary chunk data (as BSON BinData)
  
  

🧪 Example: How GridFS Stores a File

Imagine you’re uploading a 5 MB image:

• GridFS splits it into ~20 chunks (at 255 KB each).
  
  
• Each chunk goes into fs.chunks.
  
  
• Metadata goes into fs.files.

22. How does MongoDB handle transactions?

MongoDB supports multi-document ACID transactions, which means you can group multiple read and write operations into a single transaction that is atomic, consistent, isolated, and durable—just like traditional relational databases.

What is a Transaction in MongoDB?

A transaction is a sequence of operations that:

• Either all succeed or
  
  
• All rollback (fail together)
  
  

This ensures data integrity in use cases like financial applications, inventory updates, etc.

🧪 Syntax Example (Using Mongo Shell):

const session = db.getMongo().startSession();

session.startTransaction();

try {

  const usersColl = session.getDatabase(“app”).users;

  const ordersColl = session.getDatabase(“app”).orders;

  usersColl.updateOne({ _id: 1 }, { $inc: { balance: -50 } });

  ordersColl.insertOne({ userId: 1, item: “Book”, amount: 50 });

  session.commitTransaction();

} catch (error) {

  session.abortTransaction();

  print(“Transaction aborted:”, error);

} finally {

  session.endSession();

}

23. How do you delete documents?

In MongoDB, deleting documents is done using specific methods that remove data from a collection. You can delete a single document, multiple documents, or even all documents based on conditions.

1. deleteOne() – Delete a Single Document

db.users.deleteOne({ name: “John” });

🧾 Explanation:

• Deletes the first document where name is “John”.
  
  

2. deleteMany() – Delete Multiple Documents

db.users.deleteMany({ status: “inactive” });

🧾 Explanation:

• Deletes all users with status = inactive.

24. What is the role of MongoDB in AI/ML applications?

• Store unstructured or semi-structured training data
  
  
• Real-time user behavior data storage
  
  
• NoSQL flexibility suits fast-changing data schemas in ML systems
  
  

25. What are some real-world use cases of MongoDB?

• Chat apps (storing messages)
  
  
• IoT sensor data storage
  
  
• AI model logging
  
  
• E-commerce catalogs

MongoDB is an essential NoSQL database in today’s full stack and data-driven job market. This guide has covered the Top Interview Questions that every aspiring backend or data engineer must know.

These Top 25 MongoDB Interview Questions and Answers not only help you crack interviews but also strengthen your real-world implementation skills.

📌 Whether you’re preparing for your first job or upgrading your career, consistent practice with these most asked MongoDB questions will give you the edge.

Keep practicing. Stay curious. And all the best for your interview journey!

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