Atlas data federation concept in MongoDB - Mini Project: Build & Apply

Atlas Data Federation with MongoDB

📖 Scenario: You work for a company that stores customer data in multiple MongoDB collections across different clusters. You want to create a unified view of all customers using Atlas Data Federation, so you can query all data as if it were in one place.

🎯 Goal: Build a simple Atlas Data Federation query that combines customer data from two collections into one result set.

📋 What You'll Learn

Create two collections named customers_us and customers_eu with sample customer documents

Create a data federation virtual database that includes both collections

Write a query to find all customers from both collections

Filter customers with age greater than 30

💡 Why This Matters

🌍 Real World

Companies often store data in multiple databases or clusters. Atlas Data Federation lets you query all data together without moving it.

💼 Career

Understanding data federation helps in roles like data engineering and database administration where combining data from multiple sources is common.

1

Create two collections with sample customer data

Create two collections named customers_us and customers_eu with these exact documents: {"name": "Alice", "age": 28} and {"name": "Bob", "age": 35} in customers_us, and {"name": "Clara", "age": 40} and {"name": "David", "age": 25} in customers_eu.

MongoDB

// Insert documents into customers_us and customers_eu collections
// Your code here

Need a hint?

Use insertMany to add multiple documents to each collection.

2

Configure the Atlas Data Federation virtual database

Create a data federation virtual database named customerFederation that includes the collections customers_us and customers_eu from your clusters.

MongoDB

db.customers_us.insertMany([{ "name": "Alice", "age": 28 }, { "name": "Bob", "age": 35 }])
db.customers_eu.insertMany([{ "name": "Clara", "age": 40 }, { "name": "David", "age": 25 }])
// Define the data federation virtual database configuration
// Your code here

Need a hint?

Use the Atlas UI or API to create a data federation virtual database named customerFederation that includes both collections.

3

Write a query to find all customers from both collections

Write a MongoDB query on the customerFederation virtual database to find all documents from the combined collections customers_us and customers_eu.

MongoDB

db.customers_us.aggregate([
  // Your aggregation pipeline here
])

Need a hint?

Use $unionWith to combine documents from customers_us and customers_eu.

4

Filter customers with age greater than 30

Extend the query on customerFederation to only return customers whose age is greater than 30.

MongoDB

db.customers_us.aggregate([
  { $unionWith: "customers_eu" },
  // Add a filter stage here
])

Need a hint?

Add a $match stage after $unionWith to filter by age.