SQL Data Types Explained: A Comprehensive Guide for Beginners

8 min readJul 23, 2023

SQL Server data types are essential in defining the type of data that can be stored in a table column or variable. Choosing the appropriate data types is crucial for optimizing query performance, avoiding data truncation, and ensuring efficient data storage. In this comprehensive guide, we will explore the different categories of SQL Server data types, their characteristics, and best practices for usage.

Introduction to SQL Server Data Types
Exact Numeric Data Types
Approximate Numeric Data Types
Date and Time Data Types
Character Strings Data Types
Unicode Character String Data Types
Binary String Data Types
Other Data Types
Choosing the Right Data Types
Conclusion

Introduction to SQL Server Data Types

When working with SQL Server, understanding data types is crucial for designing efficient tables. Just like filling out an online form where you have to enter specific types of data, SQL Server requires you to specify the data type for each column. This ensures that the data stored in the table is consistent and can be processed correctly.

SQL Server provides a wide range of data types, including numeric, date and time, character strings, unicode character strings, binary strings, and more. Each data type has its own characteristics, such as storage size, lower and upper limits, and precision. Let’s dive deeper into each category of data types to understand their nuances.

Exact Numeric Data Types

Exact numeric data types are used to store precise numbers, such as integers, decimals, and monetary values. They are suitable for situations where exact precision is required. Here are some commonly used exact numeric data types:

Bit: The bit data type stores a binary value of 0, 1, or NULL, representing true or false. It occupies 1 byte of storage.
Int: The int data type stores whole numbers within a specific range. It occupies 4 bytes of storage and can store values from -2,147,483,648 to 2,147,483,647.
Decimal/Numeric: These data types store numbers with fixed precision and scale. Decimal and numeric are synonyms and can store values from -10³⁸+1 to 10³⁸-1.
Money/Smallmoney: Money data types are used for storing currency values with a fixed precision of four decimal places. Smallmoney is a smaller version of the money data type.

The choice of exact numeric data type depends on the range and precision required for your data. It’s essential to choose the smallest data type that can accommodate your data to save storage space.

Approximate Numeric Data Types

Approximate numeric data types are useful for storing floating-point numbers used in scientific calculations. They provide an approximate representation of the value with a certain level of precision. Here are the commonly used approximate numeric data types:

Float: The float data type is used to store floating-point numbers with a range of approximately -1.79E+308 to 1.79E+308. It occupies 4 bytes of storage.
Real: Real is a synonym for float(24) and occupies 4 bytes of storage. It provides lower precision compared to float.

When working with approximate numeric values, it’s important to consider the level of precision required for your calculations. Choosing the appropriate data type will ensure accurate results without excessive storage requirements.

Date and Time Data Types

SQL Server provides a variety of data types for storing date, time, and datetime values. These data types are widely used for managing temporal data in databases. Let’s explore the different date and time data types:

Date: The date data type stores only date values without a time component. It can store dates from January 1, 0001, to December 31, 9999. The storage size is 3 bytes.
Datetime: The datetime data type stores both date and time values. It can store dates from January 1, 1753, to December 31, 9999, with a precision of 3.33 milliseconds. It occupies 8 bytes of storage.
Datetime2: Datetime2 is an enhanced version of the datetime data type, providing a higher precision of up to 100 nanoseconds. It can store dates from January 1, 0001, to December 31, 9999, with a storage size of 6–8 bytes.
Datetimeoffset: The datetimeoffset data type stores both date and time values, along with the time zone offset. It can store dates from January 1, 0001, to December 31, 9999, with a precision of 100 nanoseconds. It occupies 10 bytes of storage.
Smalldatetime: Smalldatetime is similar to the datetime data type but provides a lower precision of one minute. It can store dates from January 1, 1900, to June 6, 2079, and occupies 4 bytes of storage.
Time: The time data type stores only time values without a date component. It provides a precision of 100 nanoseconds and can store values from 00:00:00.0000000 to 23:59:59.9999999. The storage size is 5 bytes.

Choosing the appropriate date and time data type depends on the level of precision and the range of values you need to store. Consider the specific requirements of your application when selecting a data type.

Character Strings Data Types

Character strings data types are used to store alphanumeric values such as names, addresses, and textual data. SQL Server provides several data types for character strings, each with its own storage characteristics. Let’s explore them:

Char: The char data type stores fixed-length character strings. It can store up to 8000 characters and occupies n bytes of storage, where n represents the number of characters.
Varchar: Varchar is a variable-length character string data type. It can store up to 8000 characters and occupies n bytes of storage, plus 2 bytes for overhead.
Varchar(max): Varchar(max) is similar to the varchar data type but can store up to 2³¹ characters. It occupies n bytes of storage, plus 2 bytes for overhead. However, it should be used sparingly due to its large storage requirements.
Text: The text data type is deprecated and should be avoided. It can store up to 2,147,483,647 characters and occupies n bytes of storage, plus 4 bytes for overhead.

When storing character strings, consider the maximum length required and choose the appropriate data type accordingly. Using varchar or varchar(max) is usually sufficient for most situations.

Unicode Character String Data Types

Unicode character string data types are used to store multilingual data that includes characters from different languages and scripts. These data types ensure proper storage and retrieval of Unicode data. Let’s explore the available Unicode character string data types:

Nchar: The nchar data type stores fixed-length Unicode character strings. It can store up to 4000 characters and occupies 2 times n bytes of storage.
Nvarchar: Nvarchar is a variable-length Unicode character string data type. It can store up to 4000 characters and occupies 2 times n bytes of storage, plus 2 bytes for overhead.
Ntext: The ntext data type is deprecated and should be avoided. It can store up to 1,073,741,823 characters and occupies two times the string length in bytes.

When dealing with Unicode data, it’s important to use Unicode character string data types to ensure proper storage and retrieval of multilingual content.

Binary String Data Types

Binary string data types are used to store binary data, such as images, files, and serialised objects. SQL Server provides several data types for binary strings. Let’s explore them:

Binary: The binary data type stores fixed-length binary data. It can store up to 8000 bytes of data.
Varbinary: Varbinary is a variable-length binary string data type. It can store up to 8000 bytes of data, with the actual length of the data plus 2 bytes for overhead.
Image: The image data type is deprecated and should be avoided. It can store up to 2,147,483,647 bytes of data.

Binary string data types are useful when dealing with binary data, such as images or files. Choose the appropriate data type based on the size and nature of the binary data you need to store.

Other Data Types

SQL Server provides additional data types for specific purposes. Let’s explore some of these data types:

Cursor: The cursor data type is used for variables or stored procedure output parameters that reference a cursor. It allows for navigating through query results row by row.
Rowversion: The rowversion data type returns automatically generated, unique binary numbers within a database. It is often used for concurrency control.
Hierarchyid: The hierarchyid data type is used to represent a position in a tree hierarchy. It provides efficient storage and retrieval of hierarchical data.
Uniqueidentifier: The uniqueidentifier data type stores a 16-byte GUID (Globally Unique Identifier). It is often used for uniquely identifying records.
XML: The XML data type is used to store XML data in a column or variable. It provides built-in support for querying and manipulating XML data.
Spatial Geometry Types: Spatial geometry types are used to represent data in a flat (Euclidean) coordinate system. They allow for storing and querying geometric data, such as points, lines, and polygons.
Spatial Geography Types: Spatial geography types are used to store ellipsoidal (round-earth) data, such as GPS latitude and longitude coordinates. They provide support for spherical calculations and distance measurements.
Table: The table data type is used to store a result set temporarily for processing at a later time. It is often used in functions, stored procedures, and batches.

These additional data types cater to specific requirements, such as hierarchical data, XML storage, or spatial calculations. Choose the appropriate data type based on your specific needs.

Choosing the Right Data Types

When selecting data types for your SQL Server tables, it’s important to consider several factors. Here are some best practices to guide you in choosing the right data types:

Data Accuracy: Choose data types that provide the required level of accuracy for your data. For example, if you need precise decimal values, use the decimal or numeric data types instead of float.
Storage Efficiency: Optimize storage by choosing the smallest data type that can accommodate your data. Avoid using larger data types unnecessarily, as it can lead to wasted storage space.
Performance Considerations: Consider the performance implications of your data types. Smaller data types generally require less storage and can lead to faster query execution.
Future Compatibility: Be aware of deprecated data types and avoid using them in new developments. Instead, use the recommended alternatives provided by SQL Server.
Application Requirements: Consider the specific requirements of your application. For example, if you need to store temporal data, choose the appropriate date and time data types that provide the necessary precision and range.
Internationalization: If your application needs to support multiple languages, use Unicode character string data types to store multilingual content accurately.
Data Validation: Ensure that your chosen data types align with the expected data inputs. Validate the data at the application level to prevent data truncation or errors.

By following these best practices, you can ensure efficient data storage, optimized query performance, and accurate data representation in your SQL Server tables.

Conclusion

In this comprehensive guide, we explored the various categories of SQL Server data types, including exact numeric, approximate numeric, date and time, character strings, unicode character strings, binary strings, and other specialized data types. We discussed the characteristics of each data type and provided best practices for choosing the right data types for your SQL Server tables.

By understanding the nuances of SQL Server data types and considering the specific requirements of your application, you can design efficient tables that store and process data accurately. Make informed decisions when selecting data types and regularly review and update them as your application evolves. With the right data types in place, you can ensure the integrity and performance of your SQL Server database.

Dive deeper into the world of SQL Server numeric data types and learn their characteristics, storage sizes, and precision. Find the right SQL types for your database.

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