Choosing the right data type is one of the most important decisions you make when designing a database. It's the foundation of data integrity, query performance, and storage efficiency. Pick one that's too "small," and your application crashes when data overflows. Pick one that's too "large," and you waste disk space and slow down your indexes.
In this deep dive, we’ll explore the core categories of SQL data types and learn exactly when to use each one to build lean, mean, and high-performance databases.
1. Numeric Types: The Building Blocks
Numbers are the bread and butter of most databases. But not all numbers are created equal.
Integers (Whole Numbers)
Most SQL databases offer several sizes of integers. Choosing the smallest one that safely covers your range can save significant space in large tables.
| Type | Storage | Range | Best For |
|---|---|---|---|
TINYINT | 1 byte | -128 to 127 | Status flags, ages, ratings |
INT | 4 bytes | ±2.1 billion | Most IDs, quantities |
BIGINT | 8 bytes | ±9 quintillion | Global IDs, social media likes |
Decimals and Floating Point
When you need to store parts of a whole (like money or scientific measurements), things get more interesting.
DECIMAL/NUMERIC: Exact numbers. Always use this for money.FLOAT/REAL: Approximate numbers. Great for scientific data, but dangerous for financial calculations due to rounding errors.
Tip: In many databases, 0.1 + 0.1 + ... (10 times) might not equal exactly 1.0 when using FLOAT!
2. String Types: Handling Text
Strings are flexible, but they come with specific trade-offs.
CHAR vs VARCHAR
CHAR(n): Fixed length. If you store "SQL" in aCHAR(10)column, it will be padded with spaces to 10 characters. Best for fixed-length codes like ISO country codes (US, CN, UK) or MD5 hashes.VARCHAR(n): Variable length. Only uses as much space as the text plus a small overhead. This is your go-to for names, emails, and descriptions.
TEXT and CLOB
When you need to store long-form content like blog posts or logs, use TEXT. Unlike VARCHAR, TEXT columns are often stored "off-page," which keeps your main table scans fast.
3. Date and Time: Temporal Data
Handling time correctly is notoriously difficult. SQL provides specialized types to help.
DATE: Just the date (YYYY-MM-DD). Use for birthdays or holidays.TIME: Just the time (HH:MM:SS). Use for store opening hours.TIMESTAMP/DATETIME: Both date and time. Pro Tip: Always store these in UTC to avoid time zone headaches!
4. Special Types: JSON and Booleans
Modern SQL is evolving. Many databases now support:
BOOLEAN: True or False. (SQLite uses 0 and 1).JSON/JSONB: For semi-structured data. Great for flexible user settings or API responses.
Best Practices for Choosing Types
- Be Specific, Not Generous: Don't use
VARCHAR(2000)for a username that will never exceed 50 characters. - Standardize on UTC: Never store "local time" in a database. Convert it in the application layer.
- Use the Smallest Int Possible: If you're storing a list of 50 countries, use a small code or a small integer ID.
- Avoid FLOAT for Money: Use
DECIMALorNUMERICto avoid "lost pennies" in rounding.
Conclusion
Data types are more than just "placeholders" for your data; they are the rules that govern how your database thinks and performs. By choosing the right types early, you prevent bugs, improve speed, and make your database much easier for other developers to understand.
Next time you write a CREATE TABLE statement, take a moment to ask: "Is this really the best type for this data?"
Join the Conversation
What's your biggest data type "face-palm" moment? Have you ever run out of IDs in an INT column? Let us know in the comments!