How do the data aggregation methods differ in MongoDB and PostgreSQL?

In MongoDB and PostgreSQL, data joining is implemented differently due to differences in data models and query languages.

MongoDB is a document-oriented database where data is stored in BSON format (similar to JSON). To join data from different collections, the $lookup operation is used in aggregation queries. It allows for something similar to SQL JOIN but only works with collections within the same database.

Example of joining in MongoDB:

db.orders.aggregate([
  {
    $lookup: {
      from: "products",
      localField: "product_id",
      foreignField: "_id",
      as: "product_info"
    }
  }
])

PostgreSQL is a relational DBMS where data is stored in tables. To join data, the JOIN operator (INNER JOIN, LEFT JOIN, etc.) is used, which allows combining rows from different tables based on a specified condition.

Example of joining in PostgreSQL:

SELECT orders.id, products.name
FROM orders
JOIN products ON orders.product_id = products.id;

Summary:

• In MongoDB, joining occurs through the aggregation operator $lookup and works with document collections.
• In PostgreSQL, joining is implemented via SQL JOIN and works with tables and rows.

This reflects the difference between document-oriented and relational data models.