MySQL Float vs Decimal

In MySQL, when dealing with numbers, you have two main choices: FLOAT and DECIMAL. Each has its unique strengths and best uses. Picking the right one is vital for accurate and efficient data handling in your database. Understanding their differences helps you make smart decisions for better performance and data integrity.

Difference Between Float and Decimal in MySQL

In MySQL, selecting the right numeric data types is very important for data representation and storage. Two types of data types are used in MySQL for dealing with numbers. FLOAT or DECIMAL is one of them. It is important to understand the difference between these two types of data type so that you can make the right choice based on your specific use case and requirements.

Attribute	FLOAT	DECIMAL
Precision	Approximate: Represents numbers using binary exponents, leading to potential rounding errors.	Exact: Preserves the exact value with the specified decimal places.
Storage Efficiency	Smaller storage footprint (4 bytes for FLOAT, 8 bytes for DOUBLE).	Larger storage footprint due to fixed-point representation.
Performance	Faster operations due to simpler internal handling.	Slower operations due to more complex arithmetic.
Use Cases	Suitable for scientific calculations.	Ideal for financial calculations.
Application	Less critical for precision.	Crucial for precision and accuracy.
Example	FLOAT(5, 2) means 3.14 or 123.45.	DECIMAL(5, 2) ensures exactness.

Syntax: Float, Double, and Decimal

FLOAT	FLOAT[(M,D)] .	Price FLOAT(6,2) (stores up to 6 digits, 2 decimal places).
DOUBLE	DOUBLE[(M,D)] .	Distance DOUBLE(10,4) (stores up to 10 digits, 4 decimal places).
DECIMAL	DECIMAL[(M,D)] .	Amount DECIMAL(10,2) (stores up to 10 digits, 2 decimal places).

Note: M and D denote the total number of digits and decimal places, respectively. You can omit (M,D) if no specific precision is required.

Examples with Explanation

1. DECIMAL

Let’s explore a practical example of using DECIMAL in a MySQL query:

--SQL query

CREATE TABLE products (
  product_id INT PRIMARY KEY,
  price DECIMAL(10,2) NOT NULL
);

INSERT INTO products (product_id, price) VALUES (1, 123.456789);

SELECT * FROM products;

Output:

Decimal

Explanation: The SQL code creates a table named ‘products’ with columns for product_id as the primary key and price as a decimal with two decimal places. It then inserts a record with a product_id of 1 and a price of 123.46. The SELECT statement retrieves and displays all records from the ‘products’ table.

2. FLOAT

Let’s explore a practical example of using FLOAT in a MySQL query:

 CREATE TABLE experiments (
  experiment_id INT PRIMARY KEY,
  measurement FLOAT(7,3) NOT NULL
);

INSERT INTO experiments (experiment_id, measurement) VALUES (1, 3.141592653589793);

SELECT * FROM experiments;

Output:

Float

Explanation: The SQL code creates a table ‘experiments‘ with columns for experiment_id as the primary key and measurement as a floating-point number with 7 total digits and 3 decimal places. It inserts a record with experiment_id 1 and a measurement of 3.142. The SELECT statement retrieves and displays all records from the ‘experiments‘ table.

3. Comparison of Precision

CREATE TABLE precision_comparison (
    float_value FLOAT(10, 5),
    decimal_value DECIMAL(10, 5)
);

INSERT INTO precision_comparison (float_value, decimal_value) VALUES (1234.56789, 1234.56789);

SELECT * FROM precision_comparison;

Output:

Precision

Explanation: The SQL code creates a table named ‘precision_comparison‘ with columns for float_value (FLOAT with a precision of 10 and 5 decimal places) and decimal_value (DECIMAL with a precision of 10 and 5 decimal places). It inserts a record with values (1234.56789, 1234.56789) and then retrieves and displays all records from the table. The comparison highlights the potential rounding difference between FLOAT and DECIMAL data types.

Conclusion

Depending on what you need, pick between FLOAT and DECIMAL in MySQL. If you’re doing exact calculations, like precise finances, always go for DECIMAL to avoid rounding errors. But if you’re doing scientific work where a bit of variation is okay, or if you’re concerned about storage or performance, then FLOAT is the way to go. It’s about choosing the right tool for the job based on your specific requirements.