Joins vs embedding decision in MongoDB

Introduction

Choosing between joins and embedding helps organize data efficiently in MongoDB. It affects how fast and easy it is to get related information.

When you want to keep related data together for quick access, like a blog post with its comments.

When data changes often and you want to avoid repeating updates in many places.

When related data is large or grows without limit, like a user with many orders.

When you need to query related data separately or combine data from different collections.

When you want to keep your database simple and avoid complex queries.

Syntax

MongoDB

No fixed syntax because this is a design choice:
- Embedding: store related data inside a document as nested objects or arrays.
- Referencing (joins): store related data in separate collections and link by IDs.

Embedding means putting related data inside one document.

Referencing means linking documents using IDs and combining them with queries.

Examples

Embedding address inside the user document for quick access.

MongoDB

{
  _id: 1,
  name: "Alice",
  address: {
    street: "123 Main St",
    city: "Townsville"
  }
}

Referencing address by ID to keep data separate and reusable.

MongoDB

{
  _id: 1,
  name: "Alice",
  address_id: 101
}

// In another collection:
{
  _id: 101,
  street: "123 Main St",
  city: "Townsville"
}

Sample Program

This example shows embedding orders inside the user document. It is easy to get all orders with one query.

MongoDB

db.users.insertOne({
  _id: 1,
  name: "Bob",
  orders: [
    { order_id: 1001, item: "Book", quantity: 1 },
    { order_id: 1002, item: "Pen", quantity: 3 }
  ]
})

// Query to find Bob's orders
const user = db.users.findOne({_id: 1})
user.orders

Important Notes

Embedding is good for data that is mostly read together and does not grow too big.

Referencing is better when related data is large or shared among many documents.

MongoDB does not support traditional SQL joins, but you can use $lookup for referencing.

Summary

Embedding keeps related data inside one document for fast access.

Referencing links data in separate collections for flexibility and reuse.

Choose based on how your data is used and how often it changes.