What should be the best way to store a percent value in SQL-Server?

Why DECIMAL is your new best friend

Matches percentages semantically

Every percent value inherently is a fraction of 100. The DECIMAL data type reflects this nature perfectly, storing 28% as 0.28, 100% as 1.00, and so on.

Control precision like a boss

**DECIMAL(p, s)*offers per-degree control over precision (p) and scale (s). This ensures perfect accuracy of decimal places - crucial for finance or statistical data. Just remember, with great precision comes great responsibility to fine-tune the scale.

Enforces proper boundaries

With a simple check constraint, we can guarantee that percentage values will never cross the 100% mark. This small data integrity feature can save you from a lot of headaches.

No more FLOATing problems

You won't come across the precision problems associated with floating point numbers when using DECIMAL. It gives you precision and saves you from having to deal with approximations and rounding errors. It's a win-win!

DECIMAL vs The World

Let's remember why DECIMAL is the champion when compared to FLOAT or INT for storing percentages:

• FLOAT: This data type might give you a hard time due to precision issues caused by its binary system representation. Rounding errors are not invited to this party.
• INT: Good for storing whole numbers only, but let's face it, how often are percentages whole numbers? Exactly, not very often.
• DECIMAL or NUMERIC: The unbeatable duo of SQL Server, providing fixed precision and scale, making them ideal for storing percentage data.

Scaling for precision

You need to select with thought the scale (s) and precision (p) for your DECIMAL. Some points to keep in mind:

• p should be s+1 at the very least, ensuring room for 100%.
• s controls the number of digits after the decimal point, giving precision to percentages below 100%.

Presentation layer display

Your presentation layer can convert decimal fractions to a display-friendly percentage. Simply multiply it by 100 and add a "%" sign. Accuracy on the backend, flexibility on the frontend.

Real world scenarios

Examples of different scenarios where different precisions and scales might be required:

• For mousetrap success rates, where rates usually don't exceed 100%, you can use DECIMAL(3, 2).
• For tracking your child's progress in completing their vegetables, where values could theoretically exceed 100%, you need the powerful precision of DECIMAL(5, 2).