SQL Data Types – Choosing the Right Tool for Your Data

(because age ain’t text, and names aren’t numbers)

Let’s say we’re building a users table like this:

id	name	email	age	balance	signup_date	is_active
1	Olivia	olivia@email.com	26	99.50	2024-09-20	TRUE
2	Mason	mason@mail.com	30	199.99	2023-07-12	FALSE

You’re planning this table and asking:
“What kind of stuff is going in each column?”

That’s where SQL data types come in. You’re telling the database:

• This column = text
• That one = number
• This other one = date
• And that = true/false

Based on that, here’s how we’d define the table:

CREATE TABLE users (
  id INT PRIMARY KEY AUTO_INCREMENT,
  name VARCHAR(100),
  email VARCHAR(100),
  age INT,
  balance DECIMAL(10,2),
  signup_date DATE,
  is_active BOOLEAN
);

Numeric Data Types

Type	What it stores	Example
INT	Whole numbers	1, 42, -10
BIGINT	Large numbers	9000000000
FLOAT	Decimals (approximate)	3.14
DECIMAL(p,s)	Exact decimals (like money)	99.99, 123.45

Use:

• INT for age, quantity, IDs
• DECIMAL for money, pricing
• FLOAT for averages or measurements

Text Data Types

Type	What it stores	Example
VARCHAR(n)	Variable text (max n chars)	‘Mason’, ‘Olivia’
CHAR(n)	Fixed-length text	‘Y’, ‘NY’
TEXT	Long text	Messages, bios

Use:

• VARCHAR for names, emails, cities
• TEXT for comments, articles
• CHAR for codes (like ‘M’ or ‘F’)

Date & Time Data Types

Type	Stores…	Example
DATE	Just the date	‘2025-04-03’
TIME	Just the time	’14:30:00′
DATETIME	Full date & time	‘2025-04-03 14:30:00’
TIMESTAMP	With time zone stuff	Used in logs

Use:

• DATE for birthdays, hire dates
• DATETIME for events, signups
• TIMESTAMP for time zone-sensitive tracking

Boolean Type

Type	Stores…	Values
BOOLEAN / BOOL	True/False	1 (TRUE), 0 (FALSE)

Use:

• is_active, is_deleted, is_verified — anything yes/no

Recap

• Choose your data types based on the real kind of data you’re storing
• Use INT for whole numbers, DECIMAL for money
• VARCHAR for most text, DATE for calendar things
• BOOLEAN for anything binary (yes/no)

Good data types = cleaner data + faster queries + less stress later

Next up:

Let’s see how you can find (aka filter) specific stuff in your table — like “users over 21” or “all active accounts.”
This is where the WHERE clause comes in. If you want a simple intro to filtering data in SQL, check out this beginner-friendly guide.

I’ll break it down in plain English next!