Introduction

MongoDB is a NoSQL database that stores data in flexible, JSON-like documents. This allows for faster, more efficient data storage and retrieval, especially for large-scale applications with complex data structures.

What is MongoDB?

Key Features of MongoDB:

- **Flexible Schema**: Data is stored in documents, allowing for a dynamic schema.
- **Scalability**: MongoDB supports horizontal scaling, making it suitable for large datasets.
- **Rich Queries**: Offers a rich query language with powerful features like aggregation.
- **High Performance**: Optimized for high-throughput operations and low-latency data access.
- **Replication & Fault Tolerance**: Provides redundancy and high availability with replica sets.

Setting Up MongoDB with Mongoose:

Example: Setting Up a Mongoose Model

// Install dependencies
npm install mongoose

// server.js
const mongoose = require('mongoose');

// Connect to MongoDB
mongoose.connect('mongodb://localhost:27017/mydb', {
  useNewUrlParser: true,
  useUnifiedTopology: true,
});

// Define a schema
const userSchema = new mongoose.Schema({
  name: String,
  age: Number,
  email: { type: String, required: true },
  createdAt: { type: Date, default: Date.now },
});

// Create a model
const User = mongoose.model('User', userSchema);

// Add a new user
async function createUser() {
  try {
    const user = new User({ name: 'Jane Doe', age: 25, email: 'jane.doe@example.com' });
    const result = await user.save();
    console.log('User Created:', result);
  } catch (error) {
    console.error('Error creating user:', error);
  }
}

createUser();

Performing Advanced Queries with Mongoose:

Example: Querying Data with Filters and Projections

// Find all users older than 20, return only name and email
async function findUsers() {
  try {
    const users = await User.find({ age: { $gt: 20 } }, 'name email');
    console.log('Users Found:', users);
  } catch (error) {
    console.error('Error finding users:', error);
  }
}

findUsers();

Example: Updating Documents

// Update a user's age by their name
async function updateUser() {
  try {
    const result = await User.updateOne({ name: 'Jane Doe' }, { $set: { age: 26 } });
    console.log('Update Result:', result);
  } catch (error) {
    console.error('Error updating user:', error);
  }
}

updateUser();

Example: Deleting Documents

// Delete a user by their email
async function deleteUser() {
  try {
    const result = await User.deleteOne({ email: 'jane.doe@example.com' });
    console.log('Delete Result:', result);
  } catch (error) {
    console.error('Error deleting user:', error);
  }
}

deleteUser();

Using Mongoose Middleware and Validation:

Example: Adding Custom Validation

// Define a schema with custom validation
const productSchema = new mongoose.Schema({
  name: { type: String, required: true },
  price: {
    type: Number,
    required: true,
    validate: {
      validator: (value) => value > 0,
      message: 'Price must be greater than zero',
    },
  },
});

// Create a model
const Product = mongoose.model('Product', productSchema);

// Add a new product
async function createProduct() {
  try {
    const product = new Product({ name: 'Laptop', price: -100 });
    const result = await product.save();
    console.log('Product Created:', result);
  } catch (error) {
    console.error('Validation Error:', error.message);
  }
}

createProduct();

Aggregation with Mongoose:

Example: Aggregation Pipeline

// Calculate average age of all users
async function aggregateUsers() {
  try {
    const result = await User.aggregate([
      { $group: { _id: null, averageAge: { $avg: '$age' } } }
    ]);
    console.log('Average Age:', result);
  } catch (error) {
    console.error('Aggregation Error:', error);
  }
}

aggregateUsers();

Conclusion

Using MongoDB with Mongoose simplifies complex data operations and accelerates application development.