Transactions & ACID: The Rules That Keep Data Sane
How databases protect your pipelines when everything else fails
Welcome to Day 4 of Zero2DataEngineer — this week is all about how real databases behave in production, not just in notebooks.
In data engineering, pipelines break, APIs fail, jobs timeout.
But the data itself?
That still needs to be correct.
Today we talk about how databases keep your world from falling apart — even during chaos.
What is a Transaction?
A transaction is a single unit of work in the database.
Transfer money? Transaction.
Insert a row? Transaction.
Update 3 tables in sequence? Still a transaction.
A good system either completes the transaction entirely or rolls everything back — no half-baked updates.
The ACID Model (Explained Like You’re On-Call)
Why this matters:
You don’t want to deduct money from a customer… but fail to generate the order.
You also don’t want two people editing the same record and overwriting each other’s data.
Real-Life Scenario: E-Commerce Checkout
Imagine a customer places an order. Here’s what happens:
Add a row in
ordersDeduct stock from
inventoryCharge the customer in
paymentsSend confirmation email
Without transactions, if step 3 fails after step 1 & 2 succeed…
Inventory is gone
No payment
No order shipped
No email sent
Now your support team is flooded.
With transactions, all 4 steps are wrapped in one block. If payment fails, nothing is saved.
SQL in Action
BEGIN;
INSERT INTO orders (...) VALUES (...);
UPDATE inventory SET quantity = quantity - 1 WHERE product_id = 123;
INSERT INTO payments (...) VALUES (...);
COMMIT;If anything fails before COMMIT, Postgres rolls it all back. No manual cleanup. No missing rows. No silent data corruption.