Understanding SQL Data Types: A Comprehensive Guide

Structured Query Language (SQL) is the backbone of relational database management systems (RDBMSs), enabling users to query, manipulate, and define data. One of the most fundamental concepts in SQL, and one that all SQL developers should understand, is the data type.

Whenever we create a column in SQL, we must define its data type. Similarly, when we create a variable, we define its data type.

So, why is the data type so important? Let’s find out.

Understanding Data Types in SQL

A data type defines the kind of value that a column or variable can hold. It is a necessary constraint to ensure that the data stored in a database is accurate, consistent, and relevant. Data types tell the database how much space to allocate for a value and how to interpret the data. This becomes crucial when we need to perform operations on the data or maintain data integrity.

By defining the data type of a column or variable, we are able to ensure that only a certain type of data is inserted into that column or assigned to that variable. For example, by assigning a DATE data type to a DOB (date of birth) column, we can be sure that only dates will be entered into that column. If a user attempts to enter a value that isn’t a date, then the database engine will reject it. This helps to maintain data integrity, because it eliminates the possibility that the the column will include non-date data. It narrows the values down to date values.

That’s not to say that someone could enter an invalid date, which is another possibility. In this case, we do have further tools at our disposal to eliminate this possibility. One of these is the user-defined data type, which allows us to create a data type that’s moulded to our specific requirements.

Most major RDBMSs include built-in data types (such as INTEGER, DATE, etc), while also supporting the creation of user-defined data types. User-defined data types allow us to create data types based on our own specific needs.

Examples of Common SQL Data Types

Here are some examples of the most commonly used built-in data types:

SQL Data Type	Description	Example Values
INT / INTEGER	Used for storing whole numbers. It is useful when the data doesn’t require a fractional component. Depending on the RDBMS, we can use `INT` or `INTEGER` – they both mean the same thing.	`1`, `100`, `-45`
FLOAT	Suitable for storing approximate numerical data with floating points. It is used for calculations that require decimal precision.	`3.14`, `-0.001`, `2.71828`
VARCHAR(N) / CHARACTER VARYING(N)	Used for variable-length strings, such as names, descriptions, and text content. Can store strings with a maximum length of `N`. The name we use may depend on the RDBMS, but `VARCHAR(N)` is commonly supported in most major RDBMSs.	`'Hello'`, `'SQL Query'`
CHAR(N) / CHARACTER(N) / BPCHAR(N)	Ideal for fixed-length strings, where every entry in the column has exactly `N` characters. Commonly used in cases where uniformity is required. If the string is shorter than `N`, it is padded with spaces. The precise name we use may depend on the RDBMS, but `CHAR(N)` is commonly supported across most major RDBMSs.	`'SQL '` (padded)
TEXT	Used for storing large blocks of text. It is ideal for storing long strings, such as articles, descriptions, or any kind of large textual content. Unlike `VARCHAR`, `TEXT` has no predefined limit on length.	(Large paragraphs or articles)
BOOLEAN	Represents a value that can be either true or false. Typically used in logical operations.	`TRUE`, `FALSE`
DATE	Stores calendar dates in the format `YYYY-MM-DD`. Perfect for birth dates, event dates, etc.	`2023-08-26`
TIME	Stores time information in `HH:MM:SS` format, used in scenarios like recording log times. Depending on the RDBMS and the exact data type, this could include fractional precision, with a milliseconds component.	`14:30:00`
TIMESTAMP / DATETIME / DATETIME2(N)	Combines date and time, represented in `YYYY-MM-DD HH:MM:SS` format (sometimes with a larger fractional precision depending on the type/RDBMS). Used in scenarios like logging events with precise time stamps. The precise name we use may depend on the RDBMS, and the exact specifications may differ slightly.	`2023-08-26 14:30:00`
INTERVAL	Represents a span of time, such as the difference between two dates or times. It is useful for operations that require time duration calculations.	`'1 YEAR 6 MONTHS'`, `'2 HOURS 30 MINUTES'`
BLOB	Stores Binary Large Objects. Useful for storing large binary data such as images, multimedia files, or documents.	(Binary image data)
DECIMAL(M,D)	Used for precise, fixed-point numbers where `M` is the maximum number of digits and `D` is the number of digits to the right of the decimal point. Commonly used in financial calculations where precision is critical.	`123.45`, `-0.12`

Not all RDBMSs support all data types. Also, some RDBMSs have different names for the same data type, such as seen in some of the above types.

For example, PostgreSQL supports the TIMESTAMP type, while MySQL supports both TIMESTAMP and DATETIME. SQL Server on the other hand, supports DATETIME and DATETIME2 (where DATETIME2 is basically like DATETIME, except with a larger date range, a larger default fractional precision, and optional user-specified precision).

How to Use Data Types

Here’s an example of SQL code that creates a table with multiple columns with various data types:

CREATE TABLE Employees (
    EmployeeID   INTEGER PRIMARY KEY,      -- Unique identifier for each employee
    FirstName    VARCHAR(50),              -- First name of the employee
    LastName     VARCHAR(50),              -- Last name of the employee
    Email        VARCHAR(100),             -- Email address
    BirthDate    DATE,                     -- Date of birth
    HireDate     TIMESTAMP,                -- Date and time when the employee was hired
    Salary       DECIMAL(10, 2),           -- Salary with up to 10 digits, 2 of which are after the decimal point
    IsActive     BOOLEAN,                  -- Indicates if the employee is currently active
    ProfilePhoto BLOB,                     -- Binary data for the employee's profile photo
    Notes        TEXT                      -- Long-form notes about the employee
);

That code will run in MySQL. Other RDBMSs may not support all data types or they may have different names for the data types. In any case, the syntax is generally the same – provide the column name followed by the data type.

Here’s a quick explanation of the table’s columns:

EmployeeID: An INTEGER used as the primary key, uniquely identifying each employee.
FirstName: A VARCHAR(50) field to store the employee’s first name, with a maximum length of 50 characters.
LastName: A VARCHAR(50) field to store the employee’s last name, with a maximum length of 50 characters.
Email: A VARCHAR(100) field to store the employee’s email address, with a maximum length of 100 characters.
BirthDate: A DATE field to store the employee’s date of birth.
HireDate: A TIMESTAMP field to store the exact date and time when the employee was hired.
Salary: A DECIMAL(10, 2) field to store the employee’s salary, allowing for up to 10 digits in total, with 2 digits after the decimal point.
IsActive: A BOOLEAN field to indicate whether the employee is currently active (TRUE or FALSE).
ProfilePhoto: A BLOB field to store binary data for the employee’s profile photo.
Notes: A TEXT field to store long-form notes about the employee, such as performance reviews or personal details.

This table demonstrates the use of various SQL data types, showing how they can be combined to create a suitable database schema. We know that data will conform to the rules of each data type, and we can use additional techniques to tighten these rules even further if required (such as constraints, user-defined data types, etc).

Variables

When we declare a variable, we usually need to specify which data type to use. Here’s an example of declaring variables, then setting them:

-- Declare and set variables with specific data types
DECLARE @EmployeeID INT;
DECLARE @EmployeeName VARCHAR(50);
DECLARE @Salary DECIMAL(10, 2);
DECLARE @HireDate DATE;
DECLARE @IsActive BIT;  -- BIT is often used for boolean values in SQL Server

-- Assign values to the variables
SET @EmployeeID = 101;
SET @EmployeeName = 'Butch Baddant';
SET @Salary = 55000.75;
SET @HireDate = '2023-08-26';
SET @IsActive = 1;  -- 1 for TRUE, 0 for FALSE in BIT data type

-- Example of using the variables in a query
SELECT @EmployeeID AS ID, @EmployeeName AS Name, @Salary AS Salary, @HireDate AS HireDate, @IsActive AS Active;

This code uses the syntax supported in SQL Server. Other RDBMSs may use a different syntax for declaring and setting variables. Also, as seen here, when using SQL Server, we need to use the BIT data type to represent BOOLEAN values, due to SQL Server not having a BOOLEAN type.

Consequences of Using the Wrong Data Type

Choosing the wrong data type can lead to a variety of issues:

Data Truncation: If you try to insert a value that exceeds the defined data type’s capacity, it might get truncated. For instance, inserting 'Hello World!' into a VARCHAR(5) field would result in 'Hello'.
Precision Loss: Using FLOAT instead of DECIMAL for financial data could result in precision loss, leading to inaccurate calculations.
Performance Issues: Using a larger data type than necessary (e.g., TEXT instead of VARCHAR) can lead to inefficient use of memory and slower query performance.
Data Incompatibility: Trying to insert a value that’s incompatible with the data type. For example, trying to insert 'Hello World!' into an INTEGER column would result in an error, as the data type expects a numeric value.
Logical Errors: Storing dates as VARCHAR instead of DATE can prevent proper date comparisons or calculations, leading to logical errors in the application.

Adding Constraints

While data types go a long way to restricting the type of data that can be entered into a database, they do have their limitations. The built-in data types provided with each RDBMS is designed to cater for most general scenarios. But sometimes we have scenarios where we need tighter rules on what can be entered into a column. For example, we might want a numeric value to conform to a certain format, such as a phone number. Or we may simply want to ensure that a column isn’t left blank. In such cases, we can use a constraint to help us out.

In SQL, constraints are additional rules applied to table columns to enforce data integrity and ensure that the data entered into the database meets specific requirements. Constraints further restrict the type of data that users can enter into a column, making the database more reliable and consistent.

Common Constraint Types

Here are some of the most commonly used constraints in SQL:

Constraint Type	Description	Example
PRIMARY KEY	Ensures that each value in a column (or a combination of columns) is unique and not null. It uniquely identifies each record in a table.	`EmployeeID INTEGER PRIMARY KEY`
UNIQUE	Ensures that all values in a column are unique, preventing duplicate entries.	`Email VARCHAR(100) UNIQUE`
NOT NULL	Ensures that a column cannot have a `NULL` value, meaning every record must include a value for this column.	`LastName VARCHAR(50) NOT NULL`
CHECK	Ensures that all values in a column satisfy a specific condition.	`Salary DECIMAL(10, 2) CHECK (Salary > 0)`
FOREIGN KEY	Ensures referential integrity by linking a value in one table to a value in another table.	`DepartmentID INTEGER, FOREIGN KEY (DepartmentID) REFERENCES Departments(DepartmentID)`

Example: Creating a Table with Constraints

Let’s create the Employees table again, but this time with additional constraints to enforce data integrity:

CREATE TABLE Employees (
    EmployeeID   INTEGER PRIMARY KEY,          -- Unique identifier for each employee
    FirstName    VARCHAR(50) NOT NULL,         -- First name of the employee (cannot be NULL)
    LastName     VARCHAR(50) NOT NULL,         -- Last name of the employee (cannot be NULL)
    Email        VARCHAR(100) UNIQUE,          -- Email address (must be unique)
    BirthDate    DATE,                         -- Date of birth
    HireDate     TIMESTAMP DEFAULT CURRENT_TIMESTAMP, -- Default to the current date and time
    Salary       DECIMAL(10, 2) CHECK (Salary > 0),  -- Salary must be positive
    IsActive     BOOLEAN DEFAULT TRUE,         -- Indicates if the employee is currently active (default is TRUE)
    ProfilePhoto BLOB,                         -- Binary data for the employee's profile photo
    Notes        TEXT                          -- Long-form notes about the employee
);

Explanation of constraints used in the example:

EmployeeID: The PRIMARY KEY constraint ensures that EmployeeID is unique for each employee and cannot be null. It ensures that we will be able to identify each row in the table by this column, due to it always containing a unique value – no two rows will contain the same value in this column.
FirstName and LastName: The NOT NULL constraint ensures that these columns cannot have null values, meaning each employee must have a first and last name.
Email: The UNIQUE constraint ensures that no two employees can have the same email address.
HireDate: The DEFAULT constraint assigns the current timestamp to the HireDate column if no value is provided.
Salary: The CHECK constraint ensures that the Salary value is greater than zero, preventing the entry of negative or zero salaries.
IsActive: The DEFAULT constraint sets the IsActive column to TRUE by default, indicating that new employees are active unless specified otherwise.

Benefits of Using Constraints

Data Integrity: Constraints help maintain the accuracy and consistency of data by enforcing rules that prevent incorrect or duplicate entries.
Reliability: By using constraints, you reduce the likelihood of errors in your database, making it more reliable and trustworthy.
Simplified Data Management: Constraints automate the enforcement of business rules, reducing the need for complex application logic.

Using constraints is a best practice in SQL database design, as they play a crucial role in maintaining a clean and accurate database schema.

User-Defined Data Types (UDTs)

SQL allows us to define our own data types, known as user-defined data types (UDTs). These are useful when we want to enforce consistency across multiple tables or when the existing data types don’t precisely meet our needs.

For example, you might create a user-defined type for storing phone numbers with a specific format:

CREATE DOMAIN phone_number AS VARCHAR(15) 
CHECK (VALUE ~ '^\+?[0-9]{10,15}$');

Here, phone_number is a UDT that ensures the stored value matches the pattern of a valid phone number.

Benefits of User-Defined Data Types

User-defined data types offer the following benefits:

Consistency: By defining a UDT, we can ensure that the same format is be used across different tables (by using that UDT in those tables), reducing the risk of errors.
Simplified Code: Reusing a UDT in various tables can make the schema more readable and maintainable.
Custom Constraints: UDTs allow you to enforce specific constraints that might not be possible with standard data types.

Disadvantages

While UDTs are powerful, they can introduce challenges:

Complexity: Overusing UDTs can make your database schema more complex and harder to understand.
Compatibility Issues: Not all SQL database systems fully support UDTs, which could lead to compatibility issues when migrating databases.

Conclusion

Having a good understanding of how data types work in SQL is essential for designing efficient, reliable, and accurate databases.

Choosing the correct data type for your columns not only helps to maintain data integrity but also enhances the performance and maintainability of your database. These can be combined with constraints, which provide additional restrictions on the type of data that can be entered into each column.

And user-defined data types offer yet more flexibility, allowing you to tailor the data types to your specific needs.