Node.js Setup Guide

Learn how to set up and use DocumentDB with Node.js using the official MongoDB Node.js driver.

Prerequisites

  • Node.js 14.x or later
  • npm or yarn package manager
  • DocumentDB installed and running
  • Docker installed (if set up is not completed yet)
  • Basic Node.js knowledge

Project Setup (skip if already done)

Before connecting from Node.js, make sure you have a running DocumentDB instance using Docker:

# Pull the latest DocumentDB Docker image
docker pull ghcr.io/documentdb/documentdb/documentdb-local:latest

# Tag the image for convenience
docker tag ghcr.io/documentdb/documentdb/documentdb-local:latest documentdb

# Run the container with your chosen username and password
docker run -dt -p 10260:10260 --name documentdb-container documentdb --username <YOUR_USERNAME> --password <YOUR_PASSWORD>

docker image rm -f ghcr.io/documentdb/documentdb/documentdb-local:latest

Note: Replace <YOUR_USERNAME> and <YOUR_PASSWORD> with your desired credentials. You must set these when creating the container for authentication to work.

Port Note: Port 10260 is used by default in these instructions to avoid conflicts with other local database services. You can use port 27017 (the standard MongoDB port) or any other available port if you prefer. If you do, be sure to update the port number in both your docker run command and your connection string accordingly.

Installation

  1. Creating a new Node.js project

    mkdir my-documentdb-app
    cd my-documentdb-app
    npm init -y
  2. Installing the MongoDB driver

    npm install mongodb

Connecting to DocumentDB

const { MongoClient } = require('mongodb');

const uri = 'mongodb://localhost:27017';
const client = new MongoClient(uri);

async function connect() {
  try {
    await client.connect();
    const db = client.db('your_database');
    return db;
  } catch (error) {
    console.error('Connection error:', error);
    throw error;
  }
}

Basic Operations

  1. Creating collections

    const collection = db.collection('your_collection');
  2. Document operations

    Insert operations

    // Insert a single document
    const result = await collection.insertOne({ 
      name: "John Doe", 
      email: "john@example.com", 
      created_at: new Date() 
    });
    console.log('Inserted document ID:', result.insertedId);
    
    // Insert multiple documents
    const documents = [
      { name: "Jane Smith", email: "jane@example.com" },
      { name: "Bob Johnson", email: "bob@example.com" }
    ];
    const result = await collection.insertMany(documents);
    console.log('Inserted document IDs:', result.insertedIds);

    Find operations

    // Find all documents
    const allUsers = await collection.find({}).toArray();
    console.log('All users:', allUsers);
    
    // Find with criteria
    const user = await collection.findOne({ name: "John Doe" });
    console.log('Found user:', user);
    
    // Find with projection
    const users = await collection.find({}, { 
      projection: { name: 1, email: 1, _id: 0 } 
    }).toArray();
    console.log('Users with projection:', users);
    
    // Complex queries
    const recentUsers = await collection.find({
      $and: [
        { created_at: { $gte: new Date("2025-01-01") } },
        { email: { $regex: "@example.com$" } }
      ]
    }).toArray();
    console.log('Recent users:', recentUsers);

    Update operations

    // Update a single document
    const result = await collection.updateOne(
      { name: "John Doe" },
      { $set: { status: "active" } }
    );
    console.log('Modified count:', result.modifiedCount);
    
    // Update multiple documents
    const result = await collection.updateMany(
      { email: { $regex: "@example.com$" } },
      { $set: { domain: "example.com" } }
    );
    console.log('Modified count:', result.modifiedCount);

    Delete operations

    // Delete a single document
    const result = await collection.deleteOne({ name: "John Doe" });
    console.log('Deleted count:', result.deletedCount);
    
    // Delete multiple documents
    const result = await collection.deleteMany({ status: "inactive" });
    console.log('Deleted count:', result.deletedCount);
  3. Working with indexes

    // Create a single field index
    await collection.createIndex({ email: 1 });
    console.log('Created index on email field');
    
    // Create a compound index
    await collection.createIndex({ name: 1, email: 1 });
    console.log('Created compound index on name and email');
    
    // Create a unique index
    await collection.createIndex({ email: 1 }, { unique: true });
    console.log('Created unique index on email');
    
    // Create a text index
    await collection.createIndex({ content: "text" });
    console.log('Created text index on content field');
    
    // Create a geospatial index
    await collection.createIndex({ location: "2dsphere" });
    console.log('Created geospatial index on location field');
    
    // Create a vector index
    await collection.createIndex({ 
      embedding: "vector" 
    }, { 
      vectorOptions: { dimensions: 384 } 
    });
    console.log('Created vector index on embedding field');
    
    // List all indexes
    const indexes = await collection.indexes();
    console.log('Collection indexes:', indexes);
  4. Advanced operations

    // Aggregation pipeline
    const pipeline = [
      { $match: { status: "completed" } },
      { $group: {
          _id: "$customer",
          total: { $sum: "$amount" },
          count: { $sum: 1 }
      }},
      { $sort: { total: -1 } }
    ];
    const results = await collection.aggregate(pipeline).toArray();
    console.log('Aggregation results:', results);
    
    // Vector search operations
    const vectorQuery = {
      $vectorSearch: {
        queryVector: [0.1, 0.2, 0.3],
        path: "embedding",
        numCandidates: 100,
        limit: 10
      }
    };
    const vectorResults = await collection.find(vectorQuery).toArray();
    console.log('Vector search results:', vectorResults);
    
    // Geospatial queries
    const geoQuery = {
      location: {
        $near: {
          $geometry: {
            type: "Point",
            coordinates: [-73.9667, 40.78]
          },
          $maxDistance: 1000
        }
      }
    };
    const geoResults = await collection.find(geoQuery).toArray();
    console.log('Geospatial results:', geoResults);
    
    // Text search
    const textResults = await collection.find({
      $text: { $search: "search term" }
    }).toArray();
    console.log('Text search results:', textResults);
  5. Complete example

    const { MongoClient } = require('mongodb');
    
    async function main() {
      const uri = 'mongodb://localhost:10260';
      const client = new MongoClient(uri);
    
      try {
        await client.connect();
        console.log('Connected to DocumentDB');
    
        const db = client.db('myapp');
        const collection = db.collection('users');
    
        // Create an index
        await collection.createIndex({ email: 1 }, { unique: true });
    
        // Insert documents
        const insertResult = await collection.insertMany([
          { name: "John Doe", email: "john@example.com", age: 30 },
          { name: "Jane Smith", email: "jane@example.com", age: 25 },
          { name: "Bob Johnson", email: "bob@example.com", age: 35 }
        ]);
        console.log('Inserted documents:', insertResult.insertedIds);
    
        // Find documents
        const users = await collection.find({ age: { $gte: 30 } }).toArray();
        console.log('Users 30 and older:', users);
    
        // Update a document
        const updateResult = await collection.updateOne(
          { email: "john@example.com" },
          { $set: { status: "active" } }
        );
        console.log('Updated document:', updateResult.modifiedCount);
    
        // Aggregate data
        const stats = await collection.aggregate([
          { $group: { _id: null, avgAge: { $avg: "$age" }, count: { $sum: 1 } } }
        ]).toArray();
        console.log('User statistics:', stats[0]);
    
      } catch (error) {
        console.error('Error:', error);
      } finally {
        await client.close();
        console.log('Disconnected from DocumentDB');
      }
    }
    
    main().catch(console.error);

Working with Promises and Async/Await

  1. Promise-based operations
  2. Async/await patterns
  3. Error handling
  4. Connection management

Advanced Features

  1. Bulk operations
  2. Aggregation framework
  3. Vector search
  4. Geospatial queries
  5. Change streams
  6. Transactions

Error Handling

  1. Connection errors
  2. Operation errors
  3. Timeout handling
  4. Retry strategies

Best Practices

  1. Connection pooling
  2. Query optimization
  3. Bulk operations
  4. Error handling
  5. Security considerations

Sample Applications

  1. Basic CRUD application
  2. REST API with Express
  3. Vector search example
  4. Real-time applications with change streams

Testing

  1. Setting up test environment
  2. Unit testing with Jest/Mocha
  3. Integration testing
  4. Mock testing

Deployment

  1. Development setup
  2. Production considerations
  3. Monitoring and logging
  4. Performance optimization

Next Steps

  • Explore advanced features
  • Learn about indexing strategies
  • Build your first application