Table of Contents

1. Introduction & Architecture

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WHAT IS MONGODB?
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MongoDB is an open-source, NoSQL, document-oriented database.
Instead of tables and rows (like MySQL/PostgreSQL), MongoDB stores data in flexible, JSON-like documents called BSON (Binary JSON).

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ARCHITECTURE OVERVIEW
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1. Application Layer:
   Applications connect using MongoDB Drivers (Node.js, Python, Java, etc.).

2. Database Engine (mongod):
   The primary background daemon process handling requests, data access,
   and background operations.

3. Storage Engine (WiredTiger - Default):
   Manages how data and indexes are saved to physical memory and disk.
   Provides document-level concurrency and data compression.

4. Scalability & High Availability:
   - Replica Sets: Primary/Secondary cluster for automatic failover.
   - Sharding: Horizontal partitioning to distribute large datasets across multiple nodes.

2. MongoDB Tools & Ecosystem

# 1. mongosh (MongoDB Shell)
# The modern, interactive command-line interface for querying and admin tasks.
mongosh "mongodb://localhost:27017"

# 2. MongoDB Compass
# The official GUI (Graphical User Interface) for querying, visualizing data,
# and managing indexes without writing CLI commands.

# 3. MongoDB Command-Line Database Tools:
# Export and Import collections (JSON / CSV)
mongoexport --db=shop --collection=users --out=users.json
mongoimport --db=shop --collection=users --file=users.json

# Backup and Restore entire databases (Binary BSON format)
mongodump --db=shop --out=/backups/
mongorestore --db=shop /backups/shop/

# 4. MongoDB Atlas
# The official fully managed cloud database service (AWS, Azure, GCP).

3. Core Concepts: Database, Collection, Documents

// ============================================================
// SQL vs. MongoDB Terminology Mapping
// ============================================================
//   Relational (SQL)       |   MongoDB (NoSQL)
//  ------------------------+--------------------
//   Database               |   Database
//   Table                  |   Collection
//   Row                    |   Document (BSON)
//   Column                 |   Field
//   Primary Key (PK)       |   _id (ObjectId by default)
//   JOIN                   |   $lookup / Embedded Documents

// ============================================================
// SAMPLE MONGODB DOCUMENT STRUCTURE
// ============================================================
{
  "_id": ObjectId("64f1a2b3c4d5e6f7a8b9c0d1"), // Unique Identifier
  "name": "Alice Johnson",                     // String field
  "age": 28,                                  // Number (Integer) field
  "is_active": true,                           // Boolean field
  "skills": ["JavaScript", "Python", "Docker"], // Array field
  "address": {                                 // Embedded / Sub-Document
    "city": "San Francisco",
    "country": "USA"
  }
}

4. Supported Data Types (BSON)

// MongoDB stores data as BSON, supporting standard JSON types + extended types:

1. String:      UTF-8 text               -> "Hello World"
2. Integer:     32-bit or 64-bit integer -> NumberInt(42) / NumberLong(90000000)
3. Double:      Floating point numbers   -> 19.99
4. Boolean:     Logical true or false    -> true / false
5. Array:       List of values/objects   -> ["admin", "editor"]
6. Object:      Embedded/Nested document -> { "zip": 94107 }
7. ObjectId:    12-byte unique key       -> ObjectId("...")
8. Date:        UTC DateTime             -> new Date() / ISODate("2024-01-01")
9. Null:        Empty/Undefined value    -> null
10. Binary Data:Images, files, or blobs  -> BinData(...)

5. Mongo Shell (`mongosh`) & CRUD Operations

// ============================================================
// STEP 1: Connect & Select Database
// ============================================================
//Connect
mongosh "mongodb://localhost:27017" // Switch or automatically create database use myStore; // Show current active database db; // ============================================================ // STEP 2: CREATE / INSERT // ============================================================ // Insert a single document db.products.insertOne({ name: "Wireless Mouse", price: 29.99, category: "Electronics", stock: 150, tags: ["gadgets", "computers"] }); // Insert multiple documents db.products.insertMany([ { name: "Mechanical Keyboard", price: 89.99, category: "Electronics", stock: 50 }, { name: "Coffee Mug", price: 12.50, category: "Kitchen", stock: 200 }, { name: "USB-C Cable", price: 9.99, category: "Electronics", stock: 0 } ]); // ============================================================ // STEP 3: READ / FIND // ============================================================ // Find all documents in a collection db.products.find(); // Find with exact match filter db.products.find({ category: "Electronics" }); // Find with comparison operators ($gt, $gte, $lt, $lte, $in) db.products.find({ price: { $gt: 20 } }); // Find with Projection (Include: 1, Exclude: 0) // Returns only name and price (excludes _id) db.products.find( { category: "Electronics" }, { name: 1, price: 1, _id: 0 } ); // ============================================================ // STEP 4: UPDATE // ============================================================ // Update a single document ($set updates fields without overwriting the whole document) db.products.updateOne( { name: "Wireless Mouse" }, { $set: { price: 24.99, stock: 140 } } ); // Update multiple documents db.products.updateMany( { category: "Electronics" }, { $set: { on_sale: true } } ); // ============================================================ // STEP 5: DELETE // ============================================================ // Delete a single matching document db.products.deleteOne({ name: "Coffee Mug" }); // Delete multiple matching documents db.products.deleteMany({ stock: 0 }); // Delete all documents in a collection (keeps the collection) db.products.deleteMany({});