Numeric Data Types with SQL

Numeric Data Types

Numeric data types are used to store numerical values, whether they are integers or decimal numbers. Choosing the right numeric data type is crucial for ensuring data accuracy and optimizing storage and performance.

Integer Types

Integer types are used to store whole numbers without fractional parts.

INT (or INTEGER)

• Description: Standard integer type used to store whole numbers.
• Storage: Typically uses 4 bytes (32 bits).
• Range: -2,147,483,648 to 2,147,483,647 (signed values). For unsigned integers, the range is 0 to 4,294,967,295.
• Use Case: Ideal for values within a moderate range, such as identifiers or counts.
• Example:

CREATE TABLE ExampleTable (
    Age INT
);

BIGINT

• Description: Integer type for storing larger numbers than INT.
• Storage: Typically uses 8 bytes (64 bits).
• Range: -9,223,372,036,854,775,808 to 9,223,372,036,854,775,807 (signed values). For unsigned integers, the range is 0 to 18,446,744,073,709,551,615.
• Use Case: Used for values requiring larger capacity, such as large numbers or global unique identifiers.
• Example:

CREATE TABLE ExampleTable (
    LargeNumber BIGINT
);

SMALLINT

• Description: Smaller integer type used for smaller values than INT.
• Storage: Typically uses 2 bytes (16 bits).
• Range: -32,768 to 32,767 (signed values). For unsigned integers, the range is 0 to 65,535.
• Use Case: Ideal for values within a limited range, such as status codes or small quantities.
• Example:

CREATE TABLE ExampleTable (
    SmallValue SMALLINT
);

TINYINT

• Description: Very small integer type.
• Storage: Typically uses 1 byte (8 bits).
• Range: -128 to 127 (signed values) or 0 to 255 (unsigned values).
• Use Case: Used for very small values, such as flags or quantities not exceeding 255.
• Example:

CREATE TABLE ExampleTable (
    TinyValue TINYINT
);

Decimal Numbers

Decimal types are used to store numbers with fractional parts.

FLOAT

• Description: Single-precision floating-point number type.
• Storage: Typically uses 4 bytes.
• Range: Approximately ±1.7E-308 to ±1.7E+308, with limited precision.
• Use Case: Used for calculations requiring moderate precision where slight approximation is acceptable, such as measurements or scientific calculations.
• Example: 

CREATE TABLE ExampleTable (
    Measurement FLOAT
);

DOUBLE

• Description: Double-precision floating-point number type.
• Storage: Typically uses 8 bytes.
• Range: Approximately ±2.2E-308 to ±1.8E+308, with higher precision than FLOAT.
• Use Case: Suitable for calculations requiring high precision, such as financial or scientific calculations.
• Example:

CREATE TABLE ExampleTable (
    ExactMeasurement DOUBLE
);

DECIMAL(p, s)

• Description: Fixed-point number type with specified precision (p) and scale (s).
• Storage: The precision and scale determine storage space. For example, DECIMAL(10, 2) can store up to 10 digits, with 2 digits after the decimal point.
• Range: Depends on the defined precision and scale. Provides exact precision for arithmetic operations.
• Use Case: Ideal for values where exact precision is required, such as financial amounts, prices, or interest rates.
• Example: 

CREATE TABLE ExampleTable (
    Price DECIMAL(10, 2)
);

Here, Price can store numbers with up to 10 digits total, including 2 digits after the decimal point.

Key Considerations

• Precision vs. Performance
• Precision: DECIMAL offers exact precision, which is crucial for financial calculations. FLOAT and DOUBLE provide approximations, which may be acceptable in scientific contexts but can lead to calculation errors due to approximation.
• Performance: Floating-point types (FLOAT, DOUBLE) may be faster to process compared to fixed-point types (DECIMAL), but at the cost of less exact precision.

Appropriate Usage

• Integers: Use for storing whole numbers, such as quantities or identifiers.
• Decimal Numbers: Use for values requiring a fractional part and exact precision, such as prices or interest rates.

Limits and Ranges

• Choose Based on Range: Ensure that the chosen data type can cover the range of values needed for your application.
• Storage Considerations: Larger numeric data types consume more storage space. Choose the most appropriate type based on your application’s needs.

Practical Tips

• Choose the Correct Precision: Use DECIMAL for financial data or calculations requiring exact precision.
• Check Ranges: Make sure the data type ranges match your application’s requirements.
• Avoid Approximation Errors: Be aware that floating-point types (FLOAT, DOUBLE) can introduce approximation errors in calculations.

Conclusion

Understanding and selecting the right numeric data types is essential for effective data management. By choosing the appropriate type based on the nature of the data and the precision requirements, you can optimize both performance and data accuracy in your database.