MongoDB for SQL Developers

MongoDB stores data as JSON-like documents in collections. If you know SQL, most concepts map directly; the big shift is designing around how data is read rather than normalising everything.

Vocabulary

• Table → collection.
• Row → document (stored as BSON, which adds types like dates and ObjectIds).
• Column → field; documents in a collection can have different fields.
• Primary key → _id, generated automatically if you don't set it.
• JOIN → usually embedding related data, or $lookup when needed.

CRUD with the Node.js driver

import { MongoClient } from 'mongodb';

const client = new MongoClient(process.env.MONGODB_URI);
const orders = client.db('shop').collection('orders');

// INSERT
await orders.insertOne({
  customer: { id: 7, name: 'Asha' },
  items: [{ sku: 'MUG-01', qty: 2, price: 349 }],
  status: 'paid',
  createdAt: new Date(),
});

// SELECT ... WHERE status = 'paid' AND total > 500 ORDER BY createdAt DESC LIMIT 10
const recent = await orders
  .find({ status: 'paid', 'items.price': { $gt: 300 } })
  .sort({ createdAt: -1 })
  .limit(10)
  .toArray();

// UPDATE
await orders.updateOne({ _id: orderId }, { $set: { status: 'shipped' }, $push: { history: { at: new Date(), status: 'shipped' } } });

// DELETE
await orders.deleteMany({ status: 'cancelled', createdAt: { $lt: new Date('2026-01-01') } });

Common query operators

• Comparison: $eq, $ne, $gt, $gte, $lt, $in.
• Logic: $and, $or, $not.
• Arrays: $elemMatch, $all, $size.
• Updates: $set, $unset, $inc, $push, $pull, $addToSet.

When MongoDB fits well

• Data that naturally forms documents read together (a product with variants, an order with items).
• Rapidly evolving or varied structures.
• Horizontal scaling across shards for large datasets.

For highly relational data with many cross-entity queries and strict integrity rules, a relational database is often simpler.