Is There a Money Data Type in SQL?


Larry Thompson

When working with databases, it is essential to understand the various data types available. SQL, or Structured Query Language, is a powerful tool for managing and manipulating data in relational databases.

While SQL offers a wide range of data types for storing different types of information, one might wonder if there is a specific data type for handling monetary values. In this article, we will explore whether there is a money data type in SQL and how to work with monetary values effectively.

Understanding Data Types in SQL

Before diving into the specifics of the money data type, let’s briefly review the concept of data types in SQL. Data types define the kind of data that can be stored in a column or variable. They determine how much memory space should be allocated and what operations can be performed on the stored values.

In SQL, common data types include numeric (integers, decimals), character (strings), date and time, boolean (true/false), and more. These built-in data types allow developers to store and manipulate different kinds of information accurately.

The Absence of a Money Data Type

Unlike some other database management systems like Microsoft SQL Server or PostgreSQL that provide a specific money data type, standard SQL does not define a built-in money type. Instead, it offers numeric data types such as decimal or double precision, which can effectively handle monetary values.

The absence of a dedicated money data type in standard SQL does not limit our ability to work with financial information efficiently. It simply means we need to choose an appropriate numeric type that suits our requirements when dealing with monetary values.

Precision and Scale for Monetary Values

When working with monetary values in SQL using numeric data types like decimal or double precision, it is crucial to consider the precision and scale of the chosen type. The precision refers to the total number of digits that can be stored, while the scale represents the number of digits allowed after the decimal point.

For example, if we need to store values up to a million with two decimal places, we could use the decimal(9,2) data type. This would allow us to store a range of values from -999,999.99 to 999,999.99 with two decimal places of precision.

Handling Monetary Values Effectively

To handle monetary values effectively in SQL, it is recommended to follow these best practices:

  • Choose an appropriate numeric data type: As mentioned earlier, select a numeric data type with an appropriate precision and scale for your specific needs. Consider factors such as the maximum value you anticipate storing and the level of decimal precision required.
  • Avoid floating-point types: Floating-point types like float or double precision may introduce rounding errors when working with monetary values due to their inherent imprecision.

    It is generally safer to use fixed-point types like decimal.

  • Avoid storing currency symbols: It is generally recommended not to store currency symbols (e.g., $ or €) in your database columns. Instead, consider using separate columns or metadata to denote the currency.
  • Use appropriate formatting for display: While storing monetary values in your database, it is essential to maintain consistency in formatting. Consider using fixed decimal places and formatting options specific to your programming language or framework when displaying values to users.


Although SQL does not offer a specific money data type, it provides numeric data types that can effectively handle monetary values. By choosing an appropriate numeric type with the right precision and scale, and following best practices for handling financial information, you can work with monetary values accurately and efficiently in SQL.

Remember to consider the specific requirements of your application and consult the documentation of your chosen database management system for further guidance on working with monetary values.

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