Cloud-Blog/content/blogs/8. float-make-my-dollar-float-away.md

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FLOAT Made My Dollars Float Away - FLOAT vs DECIMAL in MySQL 💸	19th Sep 2025	Recently I got a task Alter a table column from `FLOAT` to `DECIMAL(10,2)	/blogs-img/blog8.png	FLOAT Made My Dollars Float Away - FLOAT vs DECIMAL in MySQL 💸	/blogs-img/blog8.png	mysql float decimal	true

FLOAT Made My Dollars Float Away - FLOAT vs DECIMAL in MySQL

Recently I got a task:

"Alter a table column from FLOAT to DECIMAL(10,2)"

I thought: "Pff, easy task. Just run an ALTER TABLE and done. Why is this even a ticket?"

But then I read the description. Turns out, FLOAT was causing data loss, and I needed to convert it without losing data.

That’s when I realized: this isn’t just about one query. It’s about how FLOAT silently eats your money in MySQL.

Why FLOAT is a Problem

FLOAT in MySQL is a binary floating-point type. It doesn’t store exact values — only approximations.

That’s fine for rocket science 🚀 or graphics rendering 🎮, but for money where every cent matters? Disaster.

Think of FLOAT as a leaky bucket. You pour in $1,000,000.25… and it gives you back $999,999.94.

Not funny when it’s your salary.

Example of Data Loss

CREATE TABLE money_float (
    id INT AUTO_INCREMENT PRIMARY KEY,
    amount FLOAT
);

INSERT INTO money_float (amount) VALUES (1000000.25), (123456789.99);

SELECT * FROM money_float;

Result:

id	amount
1	1000000.25
2	123456792.00

We inserted 123456789.99, but got back 123456792.00. The bigger the number, the worse the corruption.

But Why Does FLOAT Lose Data?

Here’s the fun part. Let’s make it simple.

• FLOAT stores numbers in binary (base 2).
• But not every decimal number can be written exactly in binary.

Example:

• In decimal, 0.1 is simple.
• In binary, 0.1 is infinite repeating: 0.0001100110011…
• So FLOAT cuts it off at some point and stores an approximation.

That’s why when you do:

INSERT INTO money_float (amount) VALUES (0.1);
SELECT amount FROM money_float;

You might see something like 0.10000000149.

Now imagine this tiny error repeated in millions of dollars. Errors pile up, and suddenly your 9-digit amount looks… off.

DECIMAL to the Rescue

DECIMAL stores numbers differently:

• Instead of binary approximation, it stores exact digits as strings internally.
• That means 123456789.99 is stored as exactly 123456789.99.

CREATE TABLE money_decimal (
    id INT AUTO_INCREMENT PRIMARY KEY,
    amount DECIMAL(15,2)
);

INSERT INTO money_decimal (amount) VALUES (1000000.25), (123456789.99);

SELECT * FROM money_decimal;

Result:

id	amount
1	1000000.25
2	123456789.99

Perfect. ✅ No rounding surprises.

Why ALTER Won’t Save You

Here’s the trap I fell into:

ALTER TABLE money_float MODIFY amount DECIMAL(15,2);

You’d think this fixes it, right? Nope. ❌

The data was already corrupted when it was first inserted as FLOAT. ALTER just moves the already-broken value into DECIMAL.

Garbage in → garbage out.

Visual: FLOAT vs DECIMAL

FLOAT (approximation in binary):
123456789.99  --->  123456792.00 💀

DECIMAL (exact digits):
123456789.99  --->  123456789.99 ✅

Lessons Learned

• Never use FLOAT/DOUBLE for money.
• Always use DECIMAL(precision, scale) (e.g., DECIMAL(15,2)).
• If your table already has money in FLOAT, you cannot fix the lost precision with ALTER. You’ll need to re-import or clean it at the source.

Final Thought

Using FLOAT for money is like paying your salary in Monopoly money. 🎲💵 It looks okay until you try to spend it — then you realize it’s worthless.

Stick with DECIMAL, and your dollars will stay safe. ✅