Introduction to SQL Data Types

Choosing the proper data type for a table column is an important decision. It reduces the need for data type conversions, enhances the performance of database queries, and minimizes storage requirements.

In this guide, you explore the various data types that are used in relational database management systems (RDBMS). These data types can be used when creating or altering a table, or when declaring variables in database stored procedures. Some well-known RDBMS are MySQL and PostgreSQL.

SQL Binary Data Types

To store binary data (0 or 1), you use the BINARY and VARBINARY data types. The BINARY data type stores fixed-length binary data, while VARBINARY stores variable-length binary data. Both these data types are used to store strings of bits (0’s and 1’s). Their values are assigned and retrieved using hexadecimal representation, which is indicated by a prefix of 0x. The columns (or variables) of both the Binary and VarBinary data types are used to store the content of image files such as JPEG, BMP, document files, etc.

For example, for a decimal value of 63, its hexadecimal value is represented by 0x3F and its binary bit string equivalent is 111111. To understand the value of these binary strings and how they are stored, consider the example below:

1. From the command line, create a table called BinaryExample as shown below:

    CREATE TABLE BinaryExample (
      BinaryCol BINARY (10),
      VarBinaryCol VARBINARY (10)
    );
   

2. Insert a row into the BinaryExample table:

    INSERT INTO BinaryExample (BinaryCol, VarBinaryCol)
    VALUES (0x4D7953514C, 0x39274D);
   

3. Select the data from the BinaryExample table:

    SELECT BinaryCol, VarBinaryCol FROM BinaryExample;
   

   The output looks as follows:

   +------------------------+----------------------------+
   | BinaryCol              | VarBinaryCol               |
   +------------------------+----------------------------+
   | 0x4D7953514C0000000000 | 0x39274D                   |
   +------------------------+----------------------------+
       

As you can see, the BinaryCol data is padded to the maximum column size with trailing zeros, but the VarBinaryCol data column is not. This is because the columns of VarBinaryCol are defined as variable length.

SQL Numeric Data Types

The available Numeric data types can be broken up into the following groups: Integer numeric data types, Exact numeric data types, and Approximate numeric data types. The sections below discuss each group.

Integer Numeric Data Types

Integer data types can be Unsigned and Signed. Unsigned can store only zero and positive numbers, whereas Signed allows zero, positive, and negative numbers.

Most SQL implementations support Integer data types of INT, SMALLINT, and TINYINT for storage of positive and negative whole numbers. The integer numeric data type that you choose depends on the range of values that you need to store.

The following table displays the permitted storage in bytes for the integer numeric data types, and their minimum and maximum SIGNED values.

The example below demonstrates the minimum and maximum signed values of Integer numeric data types using a table named NumericExample.

1. From the command line, create the NumericExample table.

    CREATE TABLE NumericExample (
      IntColumn INT,
      SmallIntColumn SMALLINT,
      TinyIntColumn TINYINT
    );
   

2. Insert the following values into the NumericExample table.

    INSERT INTO NumericExample (IntColumn, SmallIntColumn, TinyIntColumn)
    VALUES (3258594758, 32767, 255);
   

   When you execute the above command you get an Out of range error as shown in the output below. You cannot insert the values 3258594758 and 255 to IntColumn and TinyIntColumn respectively. This is because the maximum SIGNED value for an integer data type is 2147483647 and that of a TinyInt is 127.

   ERROR 1264 (22003): Out of range value for column 'IntColumn' at row 1

3. Update the values of the IntColumn and TinyIntColumn columns and rerun the INSERT command.

    INSERT INTO NumericExample (IntColumn, SmallIntColumn, TinyIntColumn)
    VALUES (2147483647, 32767, 127);
   

4. Retrieve the column values using the SELECT statement:

    SELECT IntColumn, SmallIntColumn, TinyIntColumn
    FROM NumericExample;
   

   The output resembles the example below:

   +------------+----------------+---------------+
   | IntColumn  | SmallIntColumn | TinyIntColumn |
   +------------+----------------+---------------+
   | 2147483647 |          32767 |           127 |
   +------------+----------------+---------------+

Decimal Numeric Data Types (Exact Numeric)

The Decimal data types, DECIMAL and NUMERIC, store exact and fixed numeric values. These data types are also known as exact numeric data types. They store an integer value to the left of the decimal point and a fractional value to the right of the decimal point. They’re functionally equivalent with the same storage requirements. The storage used for these types depends on the specified precision and ranges. They can range from 2 bytes to 17 bytes, and their values can range from -10^38 +1 to +10^38 -1.

These two data types are defined by a precision and a scale. The precision denotes the number of places to the left and right of the decimal point combined, whereas the scale denotes the total number of digits to the right of the decimal point. These two data types are created using the following syntax:

DECIMAL(precision, scale)

or

NUMERIC(precision,scale)

The example below demonstrates how to create and use the decimal numeric data type.

1. From the command line, create the ExactNumericExample table.

    CREATE TABLE ExactNumericExample (
      DecimalCol DECIMAL(5,2),
      NumericCol NUMERIC(7,2)
    );
   

2. Insert the following values into the ExactNumericExample table.

    INSERT INTO ExactNumericExample (DecimalCol, NumericCol)
    VALUES (123.45, 12345.67);
   

3. Retrieve the column values using the SELECT statement:

    SELECT DecimalCol, NumericCol FROM ExactNumericExample;
   

   The output resembles the following:

   +------------+------------+
   | DecimalCol | NumericCol |
   +------------+------------+
   |     123.45 |   12345.67 |
   +------------+------------+

Floating Point Numeric Data Types (Approximate Numeric)

The Floating point numeric data types are FLOAT and REAL. They are also called approximate numeric data types. These data types store an approximate value due to the binary representation of floating point data. The syntax to create a floating point column or variable is the following:

Float(N)

The parameter N indicates whether the field should hold four or eight bytes. A value of N greater than seven requires eight bytes; seven or less requires four bytes. Floating precision for this data type ranges from -1.79E + 308 to 1.79E + 308.

Similarly, a column and variable defined as data type REAL takes up four bytes of storage, and provides a range of values from -3.40E + 38 to 3.40E + 38.

SQL Character Data Types

The data types CHAR and VARCHAR are used to store character data up to 8,000 bytes in length. Both these data types store string values in database columns, but they differ in how their values are stored and retrieved. The length of the CHAR data type remains fixed at its specified length whether that allocation space is utilized or not. If the space is not utilized, the column or variable is padded with extra spaces. VARCHAR outputs the value as it is, without any additional spaces.

The example below demonstrates the character data type.

1. From the command line, create the Employee table.

    CREATE TABLE Employee (
        LastName VARCHAR(25),
        FirstName VARCHAR(20),
        Sex CHAR(1)
    );
   

2. Insert the following values into the Employee table.

    INSERT INTO Employee (LastName, FirstName, Sex)
    VALUES ('Jones', 'Mary', 'F');
   

3. Retrieve the column values using the SELECT statement:

    SELECT LastName, FirstName, Sex FROM Employee;
   

   The output would like the following:

   +----------+-----------+------+
   | LastName | FirstName | Sex  |
   +----------+-----------+------+
   | Jones    | Mary      | F    |
   +----------+-----------+------+

The columns LastName and Firstname are declared type Varchar. This allows names to be as long as the data type definition. But for names shorter than the specified maximum, no blank spaces are appended to the data in these columns.

SQL Date and Time Data Type

The DATETIME data type is used to store the date and time values in the database. Values for the DATETIME data type use four bytes of storage for the date portion and four bytes for the time portion. The time portion of this data type specifies time with a granularity down to the number of milliseconds after midnight. Precision for this data type ranges from “January 1, 1753”, to “December 31, 9999”, with an accuracy of 3.33 milliseconds.

The example below demonstrates the DATETIME data type.

DELIMITER //
CREATE PROCEDURE Datetimedemo()
BEGIN
DECLARE BirthDate DATETIME
SET BirthDate = '1990-01-01 09:00:00'
SELECT BirthDate
END//
DELIMITER ;
call Datetimedemo;

The output resembles the following:

+----------+-----------+
| BirthDate            |
+----------+-----------+
| 1990-01-01 09:00:00  |
+----------+-----------+

SQL Data Type Considerations

When designing a database, it is extremely important to carefully select appropriate data types for table columns and stored procedure variables.

Choices made can have a significant impact on storage efficiency and overall database performance. A simple example is to define a person’s Age column to be of the Tinyint data type, as opposed to the Int data type. This is because of the following reasons:

1. As noted earlier, Tinyint data types have ¼ of the storage requirements of Int data types.
2. The retrieval efficiency of a Tinyint column versus an Int column is much greater.

On the surface, this may not appear to be of a large concern. But, if the affected table has millions of rows in it, both storage, and performance efficiencies can certainly be achieved. If you extend this design criteria across an entire database, you can generate these efficiencies by orders of magnitude.

Spending the necessary design time in database data type selection can potentially mitigate the need to perform expensive type conversions in queries and stored procedure logic, when comparing columns of different data types.

For example, in one table, you store a date in a Varchar(20)column, and in another table you store a date in a Datetime column. If you need to compare the two columns, you must use a data type conversion function in a query on one of the two columns. This is an expensive operation.

Conclusion

SQL Data Types are the attributes associated with database columns and variables. These attributes can take the form of being binary, numeric, character, and date/time. Careful design time is necessary to ensure that columns and variables are defined with a correct data type, to ensure both storage and query execution efficiency.

To learn more about SQL, see our guides on SQL joins , grouping and totaling , and SQL user management security .