MongoDB

Definition

MongoDB is a popular NoSQL document database that stores data in flexible, JSON-like documents called BSON (Binary JSON). Unlike traditional relational databases, MongoDB doesn't require a predefined schema, making it ideal for applications with evolving data requirements and rapid development cycles.

Key Features

• Document-Oriented: Stores data in flexible, JSON-like documents
• Schema-less: No predefined structure required
• Horizontal Scaling: Built-in sharding for distributed data
• Rich Query Language: Powerful querying and aggregation capabilities
• Indexing: Support for various index types for performance
• Replication: High availability through replica sets

MongoDB Operations

// Connect to MongoDB
const { MongoClient } = require('mongodb');
const client = new MongoClient('mongodb://localhost:27017');

// Insert a document
await db.collection('users').insertOne({
  name: 'John Doe',
  email: 'john@example.com',
  age: 30,
  skills: ['JavaScript', 'MongoDB', 'Node.js'],
  address: {
    street: '123 Main St',
    city: 'New York',
    zipCode: '10001'
  },
  createdAt: new Date()
});

// Find documents
const users = await db.collection('users').find({
  age: { $gte: 25 },
  skills: { $in: ['JavaScript'] }
}).toArray();

// Update a document
await db.collection('users').updateOne(
  { email: 'john@example.com' },
  { 
    $set: { age: 31 },
    $push: { skills: 'React' }
  }
);

// Delete a document
await db.collection('users').deleteOne({
  email: 'john@example.com'
});

// Aggregation pipeline
const result = await db.collection('users').aggregate([
  { $match: { age: { $gte: 25 } } },
  { $group: { 
    _id: '$city', 
    count: { $sum: 1 },
    avgAge: { $avg: '$age' }
  }},
  { $sort: { count: -1 } }
]).toArray();
                

MongoDB Query Examples

// Basic queries
db.users.find({ name: 'John Doe' })
db.users.find({ age: { $gt: 25 } })
db.users.find({ skills: { $in: ['JavaScript', 'Python'] } })

// Complex queries with operators
db.users.find({
  $and: [
    { age: { $gte: 25 } },
    { skills: { $size: { $gte: 3 } } }
  ]
})

// Text search
db.users.find({ $text: { $search: 'developer' } })

// Geospatial queries
db.locations.find({
  location: {
    $near: {
      $geometry: { type: 'Point', coordinates: [-73.9857, 40.7484] },
      $maxDistance: 1000
    }
  }
})

// Aggregation examples
db.users.aggregate([
  { $match: { age: { $gte: 25 } } },
  { $group: { 
    _id: '$department',
    totalUsers: { $sum: 1 },
    avgSalary: { $avg: '$salary' }
  }},
  { $sort: { avgSalary: -1 } },
  { $limit: 10 }
])
                

Career Impact

MongoDB vs SQL Databases

• Data Model: Document-based vs table-based structure
• Schema: Flexible schema vs rigid schema requirements
• Scaling: Horizontal scaling vs vertical scaling
• Relationships: Embedded documents vs foreign keys
• ACID: Document-level ACID vs full ACID compliance
• Query Language: MongoDB Query Language vs SQL

MongoDB Ecosystem

• MongoDB Atlas: Fully managed cloud database service
• MongoDB Compass: GUI for MongoDB database management
• Mongoose: Object modeling library for Node.js
• MongoDB Stitch: Backend-as-a-Service platform
• MongoDB Charts: Data visualization tool
• MongoDB Realm: Mobile database and sync platform

Use Cases

• Content Management: Blogs, news sites, and CMS platforms
• E-commerce: Product catalogs and user profiles
• Real-time Analytics: IoT data and user behavior tracking
• Social Networks: User profiles and activity feeds
• Mobile Applications: Offline-first mobile apps
• Gaming: Player profiles and game state management

Learning Path

1. Understand NoSQL concepts and document databases
2. Install MongoDB and learn basic CRUD operations
3. Master MongoDB query language and operators
4. Learn aggregation framework for complex queries
5. Study indexing strategies for performance optimization
6. Understand replication and sharding for scalability
7. Practice with MongoDB drivers (Node.js, Python, etc.)
8. Explore MongoDB Atlas and cloud deployment