A Simple Analogy

MongoDB is like a filing cabinet of folders. Each folder (document) contains information in whatever format makes sense—not forced into rigid columns. Files can have different structures, just like documents.

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What Is MongoDB?

MongoDB is a document-oriented NoSQL database. Data is stored as flexible JSON documents instead of rigid tables, enabling flexible schemas and faster development.

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Why Use MongoDB?

• Flexibility: Documents can have different structures
• Developer-friendly: JSON-like documents match code objects
• Scalability: Horizontal scaling with sharding
• Speed: No complex joins, data stored together
• Rapid development: Schema changes are easy

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Collections and Documents

// Collection: Users
// Document:
{
    _id: ObjectId("..."),
    name: "Alice",
    email: "alice@example.com",
    age: 30,
    tags: ["developer", "nodejs"],
    address: {
        street: "123 Main St",
        city: "NYC"
    }
}

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Basic CRUD Operations

// INSERT
db.users.insertOne({
    name: "Bob",
    email: "bob@example.com",
    age: 25
});

// FIND
db.users.findOne({ email: "bob@example.com" });
db.users.find({ age: { $gt: 25 } });  // age > 25

// UPDATE
db.users.updateOne(
    { email: "bob@example.com" },
    { $set: { age: 26 } }
);

// DELETE
db.users.deleteOne({ email: "bob@example.com" });

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Node.js Example

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

async function main() {
    const client = new MongoClient("mongodb://localhost:27017");
    
    try {
        await client.connect();
        const db = client.db("myapp");
        const users = db.collection("users");
        
        // Insert
        await users.insertOne({ name: "Charlie", age: 28 });
        
        // Find
        const user = await users.findOne({ name: "Charlie" });
        console.log(user);
        
        // Update
        await users.updateOne(
            { name: "Charlie" },
            { $set: { age: 29 } }
        );
        
        // Delete
        await users.deleteOne({ name: "Charlie" });
    } finally {
        await client.close();
    }
}

main();

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Query Operators

db.products.find({
    price: { $gte: 10, $lte: 100 },           // Range
    category: { $in: ["electronics", "books"] }, // Multiple values
    name: { $regex: "^L" },                     // Starts with L
    tags: { $all: ["new", "sale"] }             // All tags
});

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Indexes and Performance

// Create index on email (faster queries)
db.users.createIndex({ email: 1 });

// Compound index
db.orders.createIndex({ userId: 1, createdDate: -1 });

// Check query performance
db.users.find({ email: "test@example.com" }).explain("executionStats");

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Best Practices

1. Embed related data: Store address with user if always accessed together
2. Index frequently queried fields: email, userId, etc.
3. Use meaningful _id: Auto-generated ObjectId is fine
4. Validate on write: Ensure data quality
5. Plan for growth: Consider sharding strategy early

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Related Concepts to Explore

• Aggregation pipelines
• Transactions and atomicity
• Replication and sharding
• Schema validation
• Mongoose ODM for Node.js

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Summary

MongoDB provides flexible document storage ideal for rapid development. Master basic CRUD operations, queries, and indexing to build scalable applications with NoSQL databases.