MONGODB Tutorial

🧩 MongoDB Data Modeling

Data modeling in MongoDB means designing the structure of your documents and collections in a way that supports efficient storage and queries. Unlike SQL databases, MongoDB uses a flexible schema, allowing documents in the same collection to have different fields.

📦 1. Embedding vs. Referencing

• Embedding: Store related data inside a single document (faster reads).
• Referencing: Store related data in separate documents and link with _id (better for large or shared data).

✅ Best Practices

• Model data according to access patterns – store together what is queried together.
• Avoid deeply nested documents (limit depth to improve readability and performance).
• Use ObjectId references when linking documents across collections.
• Use arrays for lists (e.g. tags, comments).

🛠️ Example: Blog with Comments

👉 Embedded Model:

{
  _id: 1,
  title: "MongoDB Basics",
  content: "Learn MongoDB step-by-step...",
  comments: [
    { user: "Alice", text: "Great post!" },
    { user: "Bob", text: "Thanks!" }
  ]
}
  

👉 Referenced Model:

// posts collection
{
  _id: 1,
  title: "MongoDB Basics",
  content: "Learn MongoDB step-by-step..."
}

// comments collection
{
  _id: 101,
  postId: 1,
  user: "Alice",
  text: "Great post!"
}
  

📌 Data Modeling Scenarios

• One-to-One: Embed
• One-to-Many (small): Embed
• One-to-Many (large): Reference
• Many-to-Many: Reference both sides