SQL Server Numeric vs Decimal: What Dev Needs to Know

Hello Dev! In today’s article, we will be discussing the differences between the Numeric and Decimal data types in SQL Server. As a developer, it’s important to understand the characteristics of these data types to ensure that you’re using the right one for your particular use case. Let’s get started!

Overview of Numeric and Decimal Data Types

Before we dive into the differences between Numeric and Decimal data types, let’s first discuss what they are and how they work in SQL Server.

Data Type	Range	Storage Size
Numeric	-10^38 +1 to 10^38 -1	Depends on precision and scale
Decimal	-10^38 +1 to 10^38 -1	Depends on precision and scale

Both Numeric and Decimal are numeric data types that allow for the storage of exact or approximate values. They differ from other numeric data types, such as Integer or Float, which store values as whole numbers or in scientific notation, respectively. Numeric and Decimal data types are commonly used in financial applications, where precision is crucial to ensure accuracy in calculations.

The main difference between the two data types is their storage size. The storage size of Numeric and Decimal data types depends on the precision and scale values that are specified.

Numeric Data Type

The Numeric data type is also known as the exact numeric data type, as it stores values precisely. The Numeric data type requires two arguments: precision and scale. The precision argument specifies the total number of digits that can be stored, and the scale argument specifies the number of digits to the right of the decimal point.

For example, a Numeric data type with a precision of 10 and a scale of 2 can store values with up to 8 digits to the left of the decimal point and 2 digits to the right of the decimal point.

The storage size of the Numeric data type depends on the precision and scale values. Generally, the larger the precision and scale values, the larger the storage size required.

Advantages of Numeric Data Type

The Numeric data type has several advantages:

• Precision: The Numeric data type allows for precise storage of decimal values, ensuring accuracy in calculations.
• Compatibility: The Numeric data type is compatible with other numeric data types, allowing for easy conversions between types.

Disadvantages of Numeric Data Type

The Numeric data type also has some disadvantages:

• Storage Size: The Numeric data type has a larger storage size compared to other numeric data types.
• Performance: The larger storage size can impact performance when working with large datasets.

Decimal Data Type

The Decimal data type is similar to the Numeric data type in that it stores values precisely. The Decimal data type requires two arguments: precision and scale, which are the same as those for the Numeric data type.

For example, a Decimal data type with a precision of 10 and a scale of 2 can store values with up to 8 digits to the left of the decimal point and 2 digits to the right of the decimal point.

The storage size of the Decimal data type also depends on the precision and scale values.

Advantages of Decimal Data Type

The Decimal data type has several advantages:

• Precision: The Decimal data type allows for precise storage of decimal values, ensuring accuracy in calculations.
• Compatibility: The Decimal data type is compatible with other numeric data types, allowing for easy conversions between types.
• Flexible: The Decimal data type allows for a wider range of precision and scale values compared to the Numeric data type.

Disadvantages of Decimal Data Type

The Decimal data type also has some disadvantages:

• Storage Size: The Decimal data type has a larger storage size compared to other numeric data types.
• Performance: The larger storage size can impact performance when working with large datasets.

Numeric vs Decimal: Which One to Use?

When deciding between Numeric and Decimal data types, there are several factors to consider:

• Precision Needs: If precision is crucial for your calculations, either data type can be used. However, if you require a wider range of precision values, Decimal might be the better choice.
• Storage Size: Both data types have a larger storage size compared to other numeric data types. However, if you require a higher level of precision, you might need to sacrifice storage size.
• Performance: The larger storage size of both data types can impact performance when working with large datasets. However, using the appropriate data type and ensuring proper indexing can help mitigate this issue.

FAQ

Q: Can Numeric and Decimal data types be used interchangeably?

A: Yes, both data types can be used interchangeably, as they are both numeric data types. However, it’s important to ensure that the appropriate precision and scale values are used to ensure accurate storage of values.

Q: Can the precision and scale values for Numeric and Decimal data types be changed?

A: While the precision and scale values can be changed for both data types, it’s important to note that this can impact the storage size and accuracy of stored values. It’s recommended to carefully consider the appropriate values before making any changes.

Q: Are there any other numeric data types in SQL Server?

A: Yes, SQL Server also includes Integer, Float, Real, and Money data types, among others. These data types are used for different purposes and have different characteristics compared to Numeric and Decimal data types.

Q: Can Numeric and Decimal data types be used for calculations?

A: Yes, both data types can be used for calculations. However, it’s important to ensure that the precision and scale values are appropriate for the calculations being performed to ensure accuracy.

Q: Do Numeric and Decimal data types support negative values?

A: Yes, both data types support negative values.

Conclusion

In summary, Numeric and Decimal data types are numeric data types that allow for the storage of exact or approximate values. While Numeric and Decimal data types have several similarities, the main difference between the two data types is their storage size. As a developer, it’s important to consider the appropriate data type based on your use case and ensure that the appropriate precision and scale values are used to ensure accurate storage of values.