MongoDB Basic Interview Questions

MongoDB is a popular NoSQL database that stores data in flexible, JSON-like documents. It's designed for scalability, performance, and developer productivity.

MongoDB consists of several key components:

• Mongod: The primary daemon process for MongoDB
• Mongos: The routing service for sharded clusters
• Mongo Shell: Interactive JavaScript interface
• MongoDB Compass: GUI for database management
• MongoDB Tools: Utilities for database administration

A document in MongoDB is a data structure composed of field and value pairs. Documents are similar to JSON objects but use BSON format.

// Example Document
{
    "_id": ObjectId("507f1f77bcf86cd799439011"),
    "name": "John Doe",
    "age": 30,
    "email": "john@example.com",
    "address": {
        "street": "123 Main St",
        "city": "New York",
        "zip": "10001"
    },
    "hobbies": ["reading", "gaming", "coding"]
}

A collection is a group of MongoDB documents, similar to a table in relational databases. Collections don't enforce a schema, allowing documents within a collection to have different fields.

// Creating a collection
db.createCollection("users")

// Inserting documents into collection
db.users.insertOne({
    name: "John Doe",
    email: "john@example.com"
})

// Viewing collection documents
db.users.find()

The _id field is a unique identifier for each document in a MongoDB collection. It has the following characteristics:

• Automatically generated if not specified
• 12-byte ObjectId by default
• Guaranteed to be unique within a collection
• Indexed by default

// Example of _id field
{
    "_id": ObjectId("507f1f77bcf86cd799439011"),
    "name": "John Doe"
}

// Custom _id
{
    "_id": "user123",
    "name": "John Doe"
}

NoSQL databases are categorized into four main types:

• Document Databases: MongoDB, CouchDB
• Key-Value Stores: Redis, DynamoDB
• Column-Family Stores: Cassandra, HBase
• Graph Databases: Neo4j, OrientDB

BSON (Binary JSON) is a binary-encoded serialization of JSON-like documents used by MongoDB. It provides:

• Efficient storage and retrieval
• Support for additional data types
• Faster parsing and serialization
• Better performance than JSON

// JSON
{
    "name": "John",
    "age": 30,
    "date": "2023-01-01"
}

// BSON (conceptual)
{
    "name": "John",
    "age": 30,
    "date": ISODate("2023-01-01")
}