MySQL Float vs Decimal – What’s the Difference ? (Pros and Cons)

MySQL Float vs Decimal – What’s the Difference ? (Pros and Cons). While designing an app or application system that is going to be used as a knowledge base, there are a number of aspects that need to be taken into account. That includes a selection of appropriate data types. When storing numeric values, MySQL provides two popular data types: FLOAT and DECIMAL. They may seem to be similar, but they all have key differences in storage, accuracy and memory usage.

In this article, we take a look at MySQL Float and Decimal and discuss their differences, applications  use cases and in what situations it is better to use one data type over the other. This article allows software developers and database architectures to make a more informed choice in selecting the correct numeric data type to best meet the application’s requirements.

Shall we start with MySQL Float vs Decimal – What’s the Difference ?

What is MySQL?

Simply put MySQL is an open source relational database and serves as the primary dataset store for many well known Web sites, applications and various commercial products. In addition, it is reliable, stable and secure SQL based database management system. The purpose of the database is best suited for applications and mission critical applications or dynamic websites, and serves as an embedded database for software, hardware and devices.

MySQL Database is based on client/server architecture. A  multithreaded SQL server supporting different back ends and libraries and APIs.

MySQL use cases

  • Cloud applications.
  • Content management.
  • ECommerce solutions (Shopify).
  • SaaS platforms (ZenDesk).
  • On-prem apps with MySQL Enterprise.

What does Float mean in MySQL?

The FLOAT function is a numeric entry in MySQL that uses 4 bytes of memory to store floating point/fractional numbers. It stores approximate numeric values, including positive and negative values with fractional points. Since it is an approximate numeric data type, it does not always correspond to the exact value entered by the user.

Floating Point Types

Floating point data types are measurable numbers used to represent approximate values. Namely, for high precision calculations, use floating point data types.

Floating point kinds include:

Generally, Float represents single-precision values that use 4 bytes and contain up to 6 or 7 significant digits. On the other hand, the second component important in floating point types is double, which represent double precision values, they use 8 bytes and contain up to 15 or 16 significant digits.

What (M, D) means then? So, M is the total number of digits, while D is the number of decimal places. For example, the value 6574.345 would be read as 7.3 simply because it has 7 total digits and 3 decimal places. In addition, you also use the so-called Float (P) syntax to specify a floating-point data type where our P specifies the precision. It is assumed that P has values from 0 to 23, and is said to be a single precision column. On the other hand, similarly, if the precision is from 24 to 53, it is said to be a double precision column.

What does Decimal mean in MySQL?

Decimal is a fixed point type, which means it holds exact numeric values. Because it represents an exact number, this data type is most often used for data that is based on precise values, such as monetary data. Additionally The basic syntax is Decimal (P,D), where P refers mainly to precision (the number of digits that mean something) and D stands for scale (i.e. digits after the decimal point).

Let’s look at the maximum number of digits for precision is 65, while the maximum value for scale is 30. Moreover, if you don’t define precision or scale, the default values for P, D will be 10.0.


MySQL assigns space for integer and fractional parts separately. Also, it uses binary format to store Decimal values. The advantage is that it packs 9 digits into 4 bytes. Moreover for each part, 4 bytes are needed to store literally every multiple of 9 digits. Please take a look at the digits that are stored.

Leftover Digits Bytes

For example, DECIMAL(19,9) contains 9 digits for the fractional part and 19-9 = 10 digits for the integer part. 4 bytes are required for the fraction part. For the integer part, 4 bytes are required for the first 9 digits, and 1 additional byte is required for the remaining 1 digit. In total, the DECIMAL(19,9) column requires 9 bytes.

Comparison of MySQL Float vs Decimal - Key Differences

MySQL has two different data types for replacing floating point numbers with decimal precision: FLOAT and DECIMAL (also known as NUMBER). Although both data types store numbers with decimal precision, they both have some fundamental differences in their storage, precision, and recommended use cases. These are the main differences between MySQL FLOAT and DECIMAL.


Due to their approximate nature and binary storage format, FLOAT calculations are faster in FLOAT than DECIMAL calculations, especially for mathematical operations involving large data sets.

This arrangement results in more calculations and data storage, making DECIMAL calculations generally slower than FLOAT calculations, especially when the number of calculations is large.

Precision and Scale

It corresponds to similar numerical values and has limited accuracy. It is determined by the number of significant digits stored. So Float requires the customer to specify the accuracy and range.

It displays exact numerical values ​​and allows the user to specify precision (total number of digits) and scale (number of digits to the right of the decimal point). This makes DECIMAL particularly useful for financial calculations and applications that require high accuracy and precision.


By default range of floating data types is 24 places. Furthermore the range of decimal data types corresponds to one byte.

Floating Point Data Type

The floating data type is a single-precision, which uses the 32-bit floating-point data type. But in decimal data type, we use a 128-bit floating-point data type.

Storage Size

A floating point number that occupies 4 bytes for single precision or 8 bytes for double precision. Single-precision FLOAT numbers holds up to 7 significant digits, while double precision numbers store up to 15 significant digits.

A fixed point number that stores the specific value specified in the column declaration. The memory size depends on the resolution and scale set. It uses 1-4 bytes for each number, plus a few extra bytes for the sign and comma.


Due to their approximate nature, floating-point numbers have rounding errors and do not reflect the exact expected value, especially during calculations involving multiple operations.

With fixed point decimal precision, it stores the exact value without rounding errors. It is ideal for financial calculations or other situations where accuracy is critical.

Thank you for reading MySQL Float vs Decimal – What’s the Difference ? (Pros and Cons). We shall conclude the article.

So, DECIMAL and FLOAT both store numerical values.
Float uses approximate number data type. Not not all values in the data type range are represented exactly , so we round up the values.
Opposed to decimal which is Fixed-Precision data type. The data value of data type is represented exactly with precision and scale. There is no rounding up  the values.

MySQL Float vs Decimal – What’s the Difference ? Conclusion

Finally, deciding between MySQL Float and Decimal is not such a simple choice, as everything is determined by their use case. For approximate numeric data type whose specialty is to handle a wide range of values and the ability to tolerate inaccuracies Float is the one most apt choice. On the other hand, Decimal precision and accuracy is inevitable, and most required in financial or monetary calculations is the recommended option.

Or, more precisely, when we want to design a database schema, it is very important to accurately assess the nature of the data we are dealing with and relatively choose the right type of data. In this way, you give the possibility of reliability and, in particular, accuracy of the database while optimizing performance and storage requirements.

I hope this article provides you with the right knowledge.

Avatar for Kamil Wisniowski
Kamil Wisniowski

I love technology. I have been working with Cloud and Security technology for 5 years. I love writing about new IT tools.

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