mongodb

MongoDB - Document Database Patterns

Overview

MongoDB is a document-oriented NoSQL database that stores data in flexible, JSON-like documents. It excels at handling unstructured or semi-structured data, hierarchical relationships, and scenarios requiring horizontal scaling.

Key Features:

• Flexible schema (schemaless documents)
• Rich query language with secondary indexes
• Aggregation framework for analytics
• Horizontal scaling (sharding)
• Replica sets for high availability
• Change streams for real-time data
• Geospatial and full-text search

When to Use MongoDB:

• Rapidly evolving schemas
• Hierarchical/nested data (embedded documents)
• Real-time analytics with aggregation
• Geospatial applications
• Content management systems
• IoT data ingestion
• Catalog/inventory systems

When NOT to Use MongoDB:

• Complex multi-table joins (use RDBMS)
• ACID transactions across many documents (improved in 4.0+, but limited)
• Strict schema enforcement requirements

Schema Design Fundamentals

Document Structure

// MongoDB document (BSON format)
{
  "_id": ObjectId("507f1f77bcf86cd799439011"),  // Primary key (auto-generated)
  "email": "[email protected]",
  "name": "Alice Johnson",
  "profile": {                                   // Embedded document
    "bio": "Software developer",
    "avatar": "https://example.com/avatar.jpg",
    "social": {
      "twitter": "@alice",
      "github": "alice-dev"
    }
  },
  "tags": ["developer", "python", "mongodb"],    // Array field
  "createdAt": ISODate("2024-01-15T10:30:00Z"),
  "updatedAt": ISODate("2024-01-20T14:22:00Z")
}

Embedded vs Referenced Documents

Embedded (Denormalized) - Store related data in same document:

// Embedded: Good for 1:1 or 1:Few relationships
// User with embedded address
{
  "_id": ObjectId("..."),
  "name": "Alice",
  "address": {
    "street": "123 Main St",
    "city": "San Francisco",
    "zipCode": "94102"
  }
}

// Embedded: Order with line items (1:Many bounded)
{
  "_id": ObjectId("..."),
  "orderNumber": "ORD-2024-001",
  "customer": { "name": "Alice", "email": "[email protected]" },
  "items": [
    { "productId": "SKU001", "name": "Widget", "quantity": 2, "price": 29.99 },
    { "productId": "SKU002", "name": "Gadget", "quantity": 1, "price": 49.99 }
  ],
  "total": 109.97
}