What are Data Types in SQL Server?

Overview

One of the most critical decisions is to choose the right data type in SQL Server Database management systems that determines the kind of data that can be stored in a column or a variable. Data types can affect the performance of query execution, storage requirements, and indexing.

In this article, we will explore everything about data types in SQL, including its definition, and characteristics of all different data types supported by SQL Server.

What are Data Types in SQL Server?

Data types in SQL Server define the type of data that a column or variable can store. SQL Server provides various data types that can be used for different purposes. It is very important to choose the right data type for a column to optimize storage and performance.

What is the Importance of Data Types in SQL?

Data types are a very important component of database design in SQL. They define the structure of data and how it can be stored, processed, and retrieved. Choosing the right data type for a column or variable is important to ensure data accuracy and optimize query performance. Refer below some of the reasons why data types are crucial in SQL-

1. Data accuracy: Data types ensure that the data stored in a column of a table or variable is of the correct format and size. This prevents data corruption, data loss, and data inconsistency.
2. Query performance: Data types affect the speed and efficiency of SQL queries. Using the appropriate data type for a column or variable can significantly improve query performance by reducing the amount of data that needs to be processed.
3. Data storage: Data types determine the amount of space required to store data in a column or variable. Using the correct data type can help save disk space and reduce storage costs.

Common Data Types in SQL Server

There are mainly 9 types of data types in SQL Server as follows –

1. Exact Numeric Data Types
2. Approximate Numeric Data Types
3. Date and Time Data Types
4. Interval Data Types
5. Array Data Types
6. Character String Data Types
7. Unicode Character String Data Types
8. Binary String Data Types
9. Other Data Types

Exact Numeric Data Types

Refer to the below exact numeric data types –

1. TINYINT: The tinyint data type is a data type that can store integer values(whole numbers) from 0 to 255. It is commonly used for columns that require small integer values such as flags, statuses, or rankings. It takes a size of 1 byte on storage.
2. SMALLINT: The SMALLINT data type is a data type that can store integer values(whole numbers) from -32,768 to 32,767. It is commonly used for columns that require small integer values. It takes a size of 2 bytes on storage.
3. INT: The INT (Integer) data type is used to define a column or variable that can store integer values(whole numbers) within a larger range than the SMALLINT data type from -2,147,483,648 to 2,147,483,647. It takes a size of 4 bytes on storage.
4. BIGINT: The BIGINT data type is used to define a column or variable that can store integer values(whole numbers) within a larger range than the INT data type from -9,223,372,036,854,775,808 to 9,223,372,036,854,775,807. It takes a size of 8 bytes on storage.
5. BIT: The bit data type is a data type that can store binary data (0,1). The bit data type is useful for storing boolean values, flags, or other binary data that can be represented using a single bit of information. If there are 8 or fewer bit columns in a table, the columns are stored as 1 byte. If there are from 9 up to 16-bit columns, the columns are stored as 2 bytes, and so on.
6. NUMERIC: The numeric data type is used to define a column or variable that can store numeric values with a fixed precision and scale. The decimal data type is specified using two parameters- precision and scale. Precision is the total number of digits that can be stored, while the scale is the number of digits that can be stored to the right of the decimal point. For example, NUMERIC(5,2) can store a number with a total of 5 digits, with 2 of those digits to the right of the decimal point. The decimal data type is commonly used for storing monetary values or other numeric data that require a fixed number of decimal places. It provides greater accuracy than the FLOAT or REAL data types but requires more storage space. It takes a size of 5 to 17 bytes on storage.
7. DECIMAL: The decimal data type is used to define a column or variable that can store numeric values with a fixed precision and scale. The decimal data type is specified using two parameters: precision and scale. Precision is the total number of digits that can be stored, while the scale is the number of digits that can be stored to the right of the decimal point. For example, NUMERIC(5,2) can store a number with a total of 5 digits, with 2 of those digits to the right of the decimal point. The decimal data type is commonly used for storing monetary values or other numeric data that require a fixed number of decimal places. It provides greater accuracy than the FLOAT or REAL data types but requires more storage space. It takes a size of 5 to 17 bytes on storage.
8. MONEY: The MONEY data type is used to define a column or variable that can store monetary values. The MONEY data type stores currency values with a precision of 19 digits, with 4 digits to the right of the decimal point. It is commonly used for storing monetary values such as salaries, prices, or other financial data. The MONEY data type is similar to the DECIMAL data type, but it is optimized for storing monetary values specifically. It takes up 8 bytes of storage and can store values ranging from -922,337,203,685,477.5808 to 922,337,203,685,477.5807. Note that the MONEY data type is specific to Transact-SQL, which is used in Microsoft SQL Server. Other SQL implementations may use different data types for storing monetary values. It takes a size of 8 bytes on storage.
9. SMALLMONEY: The SMALLMONEY data type is used to define a column or variable that can store small monetary values with a reduced precision compared to the MONEY data type. The SMALLMONEY data type stores currency values with a precision of 10 digits, with 4 digits to the right of the decimal point. It is commonly used for storing monetary values such as prices or other financial data that do not require the precision of the MONEY data type. The SMALLMONEY data type takes up 4 bytes of storage and can store values ranging from -214,748.3648 to 214,748.3647. It is specific to Transact-SQL, which is used in Microsoft SQL Server. Other SQL implementations may use different data types for storing small monetary values. It takes a size of 4 bytes on storage.

Approximate Numeric Data Types

Refer to the below approximate numeric data types –

1. FLOAT: The FLOAT data type is used to define a column or variable that can store approximate numeric values with variable precision. The FLOAT data type can store floating-point values in scientific notation, with a precision of up to 53 bits. It is commonly used for storing numeric data that requires a large range of values and precision, such as scientific measurements or astronomical data. The FLOAT data type can store values ranging from -1.79E+308 to 1.79E+308, with a storage size of 4 or 8 bytes, depending on the specific implementation of SQL. It provides greater flexibility and efficiency than the NUMERIC or DECIMAL data types but may be less precise due to its floating-point nature.

2. REAL: The REAL data type is used to define a column or variable that can store approximate numeric values with fixed precision. The REAL data type can store floating-point values in scientific notation, with a precision of up to 24 bits. It is commonly used for storing numeric data that requires a large range of values and precision, such as scientific measurements or astronomical data. The REAL data type can store values ranging from -3.40E+38 to 3.40E+38, with a storage size of 4 bytes. It provides greater flexibility and efficiency than the NUMERIC or DECIMAL data types but may be less precise due to its floating-point nature. Note that the REAL data type is specific to Transact-SQL, which is used in Microsoft SQL Server. Other SQL implementations may use different data types for storing approximate numeric values.

Date and Time Data Types

Refer to the below date and time data types –

1. DATE: The DATE data type is used to define a column or variable that can store date values. The DATE data type stores date values in the format of YYYY-MM-DD. The DATE data type takes up 3 bytes of storage and can store values ranging from January 1, 0001 to December 31, 9999.
2. TIME: The TIME data type is used to define a column or variable that can store time values. The TIME data type stores time values in the format of HH:MM:SS.ssssss, where HH is the hour in 24-hour format. The TIME data type takes up 5 bytes of storage and can store values ranging from 00:00:00.0000000 to 23:59:59.9999999.
3. DATETIME: The DATETIME data type is used to define a column or variable that can store date and time values. The DATETIME data type stores date and time values in the format of YYYY-MM-DD HH:MM:SS.sss, where YYYY is the year, MM is the month, DD is the day, HH is the hour in 24-hour format, MM is the minute, SS is the second, and sss is the fractional seconds. The DATETIME data type takes up 8 bytes of storage and can store values ranging from January 1, 1753, to December 31, 9999.
4. DATETIME2: The DATETIME2 data type is used to define a column or variable that can store date and time values with high precision. The DATETIME2 data type stores date and time values in the format of YYYY-MM-DD HH:MM:SS.sssssss, where YYYY is the year, MM is the month, DD is the day, HH is the hour in 24-hour format, MM is the minute, SS is the second, and sssssss is the fractional seconds. The DATETIME2 data type takes up between 6 and 8 bytes of storage, depending on the precision of the fractional seconds, and can store values ranging from January 1, 0001, to December 31, 9999.
5. SMALLDATETIME: The smalldatetime data type is used to define a column or variable that can store date and time values with a reduced precision compared to the DATETIME data type. The SMALLDATETIME data type stores date and time values in the format of YYYY-MM-DD HH:MM:SS, where YYYY is the year, MM is the month, DD is the day, HH is the hour in 24-hour format, MM is the minute, and SS is the second. The SMALLDATETIME data type takes up 4 bytes of storage and can store values ranging from January 1, 1900, to June 6, 2079.
6. DATETIMEOFFSET: The datetimeoffset data type is used to define a column or variable that can store date and time values along with the corresponding time zone offset. The datetimeoffset data type stores date and time values in the format of YYYY-MM-DD HH:MM:SS.ssssss +|-hh:mm, where YYYY is the year, MM is the month, DD is the day, HH is the hour in 24-hour format, MM is the minute, SS is the second, ssssss is the fractional seconds, and +|-hh:mm represents the time zone offset from Coordinated Universal Time (UTC). It is commonly used for storing timestamps that require both the date and time as well as the corresponding time zone information, such as flight schedules or global trading data. The datetimeoffset data type takes up 10 bytes of storage and can store values ranging from January 1, 1 CE, to December 31, 9999 CE, with a precision of up to six decimal places for the fractional seconds. It supports a range of date and time-related functions, such as date and time arithmetic, date and time formatting, date and time comparisons, as well as functions specific to handling time zone information.

7. TIMESTAMP: The TIMESTAMP data type is used to define a column or variable that can store a binary value representing a unique identifier for a version of a row in a table. The TIMESTAMP data type is automatically generated and updated whenever a row in a table is inserted or updated. It is commonly used for tracking changes to data in a database, such as keeping track of when a record was last updated or who made the update. The TIMESTAMP data type takes up 8 bytes of storage and is represented as a binary value. It is not related to date and time values, despite its name. In some versions of SQL, the TIMESTAMP data type has been replaced with the row version data type.

Interval Data Types

Refer to the below interval data types –

1. INTERVAL DAY: The INTERVAL DAY data type is used to define a period of time measured in days, hours, minutes, and seconds. The INTERVAL DAY data type is used to represent a duration of time between two points in time, such as the time elapsed between two events or the duration of a task. It can be added or subtracted from a date or timestamp value to calculate a new date or timestamp value. The INTERVAL DAY data type takes up 12 bytes of storage and can store values ranging from -999999999 to 999999999 days, with a precision of up to nine decimal places for the fractional seconds. It supports a range of date and time-related functions, such as date and time arithmetic, date and time formatting, and date and time comparisons.

2. INTERVAL MONTH: The INTERVAL MONTH data type is used to define a period of time measured in months and years. The INTERVAL MONTH data type is used to represent a duration of time between two points in time, such as the time elapsed between two events or the duration of a task. It can be added or subtracted from a date or timestamp value to calculate a new date or timestamp value. The INTERVAL MONTH data type takes up 8 bytes of storage and can store values ranging from -999999999 to 999999999 months, with no fractional precision. It supports a range of date and time-related functions, such as date and time arithmetic, date and time formatting, and date and time comparisons.

3. INTERVAL YEAR: The INTERVAL YEAR data type is used to define a period of time measured in years. The INTERVAL YEAR data type is used to represent a duration of time between two points in time, such as the time elapsed between two events or the duration of a task. It can be added or subtracted from a date or timestamp value to calculate a new date or timestamp value. The INTERVAL YEAR data type takes up 4 bytes of storage and can store values ranging from -999999999 to 999999999 years, with no fractional precision. It supports a range of date and time-related functions, such as date and time arithmetic, date and time formatting, and date and time comparisons.

Array Data Types

Refer to the below array data types –

1. JSON: The JSON data type is used to store and manipulate JSON (JavaScript Object Notation) data within a relational database. JSON is a lightweight data interchange format that is commonly used in web applications to transmit data between a server and a client. The JSON data type in SQL allows for storing and querying JSON data within a table column or variable. It can be used to store and manipulate JSON documents of various complexities, such as arrays, objects, strings, numbers, and boolean values. The JSON data type supports a wide range of JSON-related functions, such as JSON_VALUE, JSON_QUERY, JSON_MODIFY, and many others. These functions allow for querying, searching, and modifying JSON data stored within a database column or variable. It takes a size 2 GB of storage.

Character String Data Types

Refer to the below character string data types –

1. CHAR: The CHAR data type is used to store fixed-length character strings of a specified length. The length of a CHAR column or variable is specified when it is created, and any values inserted into the column or variable must be of the same length. For example, if a CHAR(10) column is created, any values inserted into the column must be exactly 10 characters long. If a value shorter than 10 characters is inserted, it will be padded with spaces to fill the remaining characters. If a value longer than 10 characters is inserted, an error may be generated or the value may be truncated. CHAR columns and variables are useful for storing values that have a fixed length, such as postal codes or phone numbers, where the length of the value is always the same. Compared to VARCHAR columns and variables, which are used for storing variable-length strings, CHAR columns, and variables may have slightly better performance for certain operations, such as sorting or grouping. Max size of char is 8,000 characters.

2. VARCHAR: The VARCHAR data type is used to store variable-length character strings. The “VAR” in VARCHAR stands for “variable”, which means that the length of the value can vary up to a maximum specified length. The length of a VARCHAR column or variable is specified when it is created, and values inserted into the column or variable can have a length up to the maximum specified length. Unlike the CHAR data type, VARCHAR columns and variables can store values of different lengths. For example, if a VARCHAR(50) column is created, values inserted into the column can have a length of up to 50 characters. If a value shorter than 50 characters is inserted, it will be stored as is without any padding. If a value longer than 50 characters is inserted, the value will be truncated to fit within the column. VARCHAR columns and variables are useful for storing text data that may vary in length, such as names, descriptions, or messages. The ability to store variable-length strings can be more efficient in terms of storage space than using a CHAR data type. Max size of a varchar is 8,000 characters and takes the storage of 2 bytes plus a number of characters.

3. VARCHAR(MAX): The VARCHAR(MAX) data type is used to store variable-length character strings that can be up to 2^31-1 characters long. The “VAR” in VARCHAR stands for “variable”, which means that the length of the value can vary up to a maximum specified length, which in this case is very large. The VARCHAR(MAX) data type is often used to store large text data, such as articles, blog posts, or other documents, where the length of the content may vary greatly. Unlike the regular VARCHAR data type, which has a maximum length specified when it is created, the VARCHAR(MAX) data type can store values of any length up to its maximum capacity. The storage requirements for VARCHAR(MAX) columns may depend on the specific implementation of the database or server. In general, the storage required for a VARCHAR(MAX) column is equal to the length of the value being stored multiplied by the size of each character in the character set being used. However, some databases may store VARCHAR(MAX) columns differently than regular VARCHAR columns, such as using a separate storage mechanism for large values. Max size of varchar(max) is 1,073,741,824 characters and takes the storage of 2 bytes plus a number of characters.

4. TEXT: The TEXT data type is used to store large variable-length character strings. Unlike the VARCHAR data type, which has a maximum length specified when it is created, the TEXT data type can store values of any length up to its maximum capacity. The maximum size of a TEXT column depends on the specific implementation of the database or server, but it is typically larger than the maximum size of a regular VARCHAR column. The TEXT data type is often used to store large text data, such as articles, blog posts, or other documents, where the length of the content may vary greatly. The storage requirements for TEXT columns may depend on the specific implementation of the database or server. In general, the storage required for a TEXT column is equal to the length of the value being stored multiplied by the size of each character in the character set being used. Max size of a text is 2GB of text data and takes the storage of 4 bytes plus a number of characters.

Unicode Character String Data Types

Refer to the below Unicode character string data types –

1. NCHAR: The NCHAR data type is used to store fixed-length Unicode character strings. Unicode is a character encoding standard that supports a wide range of characters and symbols from different writing systems around the world. The NCHAR data type is similar to the CHAR data type, but it is designed to store Unicode characters instead of ASCII characters. When an NCHAR column is created, you must specify the length of the column in terms of the number of characters it can hold. For example, an NCHAR(10) column can store up to 10 Unicode characters. If you attempt to store more than the specified number of characters in an NCHAR column, the database will raise an error. The storage requirements for an NCHAR column depend on the length of the column and the implementation of the database or server. In general, each character in an NCHAR column requires two bytes of storage. For example, an NCHAR(10) column requires 20 bytes of storage. The NCHAR data type is commonly used in international applications where it is necessary to support a wide range of languages and writing systems. Because it is designed to store Unicode characters, the NCHAR data type can be used to store text in any language, including languages that use non-Latin scripts.

2. NVARCHAR: The NVARCHAR data type is used to store variable-length Unicode character strings. The “N” in NVARCHAR stands for “National”, which indicates that the data is encoded in Unicode. The length of an NVARCHAR column or variable is specified when it is created, and values inserted into the column or variable can have a length up to the maximum specified length. Unlike the CHAR data type, NVARCHAR columns and variables can store values of different lengths. For example, if an NVARCHAR(50) column is created, values inserted into the column can have a length of up to 50 characters. If a value shorter than 50 characters is inserted, it will be stored as is without any padding. If a value longer than 50 characters is inserted, the value will be truncated to fit within the column. NVARCHAR columns and variables are useful for storing text data that may vary in length, such as names, descriptions, or messages. The ability to store variable-length strings can be more efficient in terms of storage space than using a CHAR data type.

3. NVARCHAR(MAX): The NVARCHAR(MAX) data type is used to store variable-length Unicode character strings of up to 2^31-1 (2,147,483,647) characters. The NVARCHAR(MAX) data type is similar to the NVARCHAR data type, but it allows you to store much larger strings. When an NVARCHAR(MAX) column is created, you do not need to specify a length for the column. Instead, the length of the column is determined dynamically based on the length of the data being stored. This means that an NVARCHAR(MAX) column can store data of varying length, up to the maximum length of 2^31-1 characters. The storage requirements for an NVARCHAR(MAX) column depend on the length of the data being stored. If the length of the data is less than or equal to 4000 characters, the data is stored in the same way as an NVARCHAR column. If the length of the data is greater than 4000 characters, the data is stored in a special storage area called the Large Object Storage (LOB) area. The NVARCHAR(MAX) data type is commonly used when you need to store large amounts of text data, such as long documents or descriptions. Because it is designed to store Unicode characters, the NVARCHAR(MAX) data type can be used to store text in any language, including languages that use non-Latin scripts.

4. NTEXT: The NTEXT data type is used to store large variable-length Unicode character strings of up to 2^30-1 (1,073,741,823) characters. The NTEXT data type is similar to the NVARCHAR data type, but it is designed to handle much larger strings. When an NTEXT column is created, you do not need to specify a length for the column. Instead, the length of the column is determined dynamically based on the length of the data being stored. This means that an NTEXT column can store data of varying lengths, up to the maximum length of 2^30-1 characters. The storage requirements for an NTEXT column depend on the length of the data being stored. If the length of the data is less than or equal to 4000 characters, the data is stored in the same way as an NVARCHAR column. If the length of the data is greater than 4000 characters, the data is stored in a special storage area called the Large Object Storage (LOB) area. The NTEXT data type is commonly used when you need to store large amounts of text data, such as long documents or descriptions. Because it is designed to store Unicode characters, the NTEXT data type can be used to store text in any language, including languages that use non-Latin scripts. However, it is now deprecated in SQL Server and Microsoft recommends using NVARCHAR(MAX) instead.

Binary String Data Types

Refer to the below binary string data types –

1. BINARY: The BINARY data type is used to store fixed-length binary data. This means that the size of the data being stored is fixed and cannot be changed. The BINARY data type is typically used to store data that is a fixed size, such as images, audio files, or other binary data. When a BINARY column is created, you must specify the size of the column in bytes. For example, if you want to store a 10-byte image file in a BINARY column, you would create the column with a size of 10 bytes. The storage requirements for a BINARY column depend on the size of the column. If the size of the column is N bytes, then each row in the table will require N bytes of storage. The BINARY data type is different from the VARBINARY data type in that the size of the data being stored in a VARBINARY column can be variable, whereas the size of the data being stored in a BINARY column is fixed. The VARBINARY data type is often used to store binary data that has a variable length.

2. VARBINARY: The VARBINARY data type is used to store variable-length binary data. This means that the size of the data being stored can vary, unlike the BINARY data type where the size of the data is fixed. The VARBINARY data type is typically used to store binary data such as images, audio files, or other binary data where the size of the data may vary. When a VARBINARY column is created, you do not need to specify the size of the column in bytes. Instead, you can specify a maximum size for the column using a number, such as VARBINARY(100) to indicate that the maximum size of the column is 100 bytes. The storage requirements for a VARBINARY column depend on the actual size of the data being stored in each row. If a row has a VARBINARY column with 50 bytes of data, then that row will require 50 bytes of storage. The VARBINARY data type is similar to the BINARY data type but is more flexible because it allows for variable-length data to be stored. However, the flexibility comes at a cost because the storage requirements can be higher than for the BINARY data type, especially if many rows have columns with large amounts of data. Max size of the varbinary is 8,000 characters. Overall, the VARBINARY data type is useful for storing binary data where the size may vary, but may not be the best choice for storing fixed-length binary data.

3. VARBINARY(MAX): The varbinary(max) data type in SQL Server is used to store binary data in a variable length format, where the maximum length of the data can be up to 2^31-1 bytes. It is similar to the varbinary data type but with no maximum length restriction. The varbinary(max) data type is often used to store large binary objects (BLOBs) such as images, video, audio, and other multimedia files. It is also used to store serialized data or encrypted data. When varbinary(max) data is stored in a table, SQL Server stores a pointer to the actual data on disk, rather than storing the data directly in the table. This allows for efficient storage and retrieval of large amounts of binary data. Max size of varbinary(max) is 2 GB. Note that the max specifier for varbinary and nvarchar data types was introduced in SQL Server 2005. Prior to that, the maximum length of these data types was limited to 8000 bytes.

4. IMAGE: The image data type in SQL Server is used to store binary data in a fixed length format, where the maximum length of the data is 2^31-1 bytes. It is similar to the varbinary(max) data type, but it has been deprecated since SQL Server 2005 and replaced by the varbinary(max) data type. The image data type is often used to store large binary objects (BLOBs) such as images, video, audio, and other multimedia files. When image data is stored in a table, SQL Server stores the data directly in the table, rather than storing a pointer to the actual data on disk. This can result in slower performance when dealing with large amounts of binary data. Max size of varbinary(max) is 2 GB. It is recommended to use the varbinary(max) data type instead of image for storing large binary objects in SQL Server.

Other Data Types

Refer to the below other data types –

1. CURSOR: In SQL, a cursor is a database object used to manipulate a set of rows returned by a query. It is used to perform operations such as fetching data one row at a time, iterating through the rows, and updating or deleting rows. A cursor is declared and defined within a stored procedure or a SQL script using the DECLARE CURSOR statement. The DECLARE CURSOR statement includes the name of the cursor, the query that defines the set of rows to be processed, and optional parameters that control the behavior of the cursor such as whether it is read-only or updatable, and the direction in which it can be scrolled. Once a cursor is defined, it can be opened using the OPEN statement. After opening a cursor, you can use the FETCH statement to retrieve the next row from the result set, and then perform any necessary processing or manipulation of that row. The FETCH statement can be used in a loop to process all rows returned by the query. After processing all rows, the cursor can be closed using the CLOSE statement and then deallocated using the DEALLOCATE statement.

2. HIERARCHYID: The hierarchyid data type is a special data type in SQL Server that represents a hierarchical structure of data. It is used to store tree-like structures, such as organization charts or file directories, where each node has a parent and zero or more children. The hierarchyid data type is a variable-length binary data type that can store values up to 892 bytes in length. It supports a wide range of operations for querying and manipulating the hierarchical data, including methods for navigating the tree structure, performing node comparisons, and creating new nodes. The hierarchyid data type is unique to SQL Server and is not part of the SQL standard. It was introduced in SQL Server 2008 and is commonly used in applications that need to store and query hierarchical data efficiently.

3. SQL_VARIANT: The sql_variant data type in SQL Server is a special data type that can store values of various other SQL Server data types. It allows for the storage of values of different data types in a single column of a table or a parameter of a stored procedure or function. The sql_variant data type can store values of any data type supported by SQL Server, including numeric, character, datetime, binary, and other data types. However, there are some limitations to using this data type. Firstly, it has a maximum size of 8,016 bytes of various data types except for text, ntext, and timestamp, which means that it cannot store very large values. Secondly, it cannot be used in the following situations-a. As a key column in an index. b. As a parameter or return value for a CLR user-defined function or stored procedure. c. In a distributed query or in a query with a UNION operator that involves more than one server. Despite its limitations, the sql_variant data type can be useful in certain scenarios where you need to store values of different data types in the same column or parameter.

4. SPATIAL DATA TYPES: Spatial data types in SQL Server are used to store geospatial data, such as points, lines, polygons, and other spatial objects. They allow for the storage, retrieval, and analysis of data related to geography or location. The spatial data types in SQL Server include geometry and geography. The geometry data type is used to represent planar (flat) geometric objects, such as points, lines, and polygons. It is based on the Euclidean coordinate system, which uses x and y coordinates to represent points on a 2D plane. The geography data type, on the other hand, is used to represent data in a round-earth coordinate system. It allows for the storage and manipulation of data related to locations on the Earth’s surface, such as latitude, longitude, and elevation. Geography data type supports the calculation of distances between points, areas of regions, and the intersection of spatial data with real-world data like roads or rivers. POINT, LINE and POLYGON are examples.

5. TABLE: The table is a special data type that is used to store a result to view or process later in time. It is used to store temporarily rows that return as the table-valued function. Variables and functions can be declared table types that can be used in batches, stored procedures, and functions. To declare table type variable, use DECLARE @local_variable;
6. ROWVERSION: The row version data type in SQL Server is used to store a binary number that is automatically updated every time a row is inserted or updated in a table. This data type was previously called a timestamp, but its name was changed to avoid confusion with the timestamp data type used for date and time values. The row version data type is commonly used to implement optimistic concurrency control in SQL Server, where multiple users can simultaneously access and modify the same data without interfering with each other’s changes. When a row is updated, the row version value is automatically incremented, so that subsequent updates can check whether the row has been changed by another user since it was last read. The row version data type is always 8 bytes in size, and its value is a binary representation of a 64-bit unsigned integer. It cannot be assigned a value directly but is instead updated automatically by SQL Server. The row version data type can be used in the PRIMARY KEY or UNIQUE constraints of a table, but it cannot be used as a foreign key reference.

7. UNIQUEIDENTIFIER: The unique identifier data type in SQL Server is used to store a 128-bit globally unique identifier (GUID). A GUID is a unique value generated by an algorithm that ensures its uniqueness across all computers and networks. A GUID value is represented by a 32-character hexadecimal string, typically displayed with hyphens separating the groups of characters (e.g. 6F9619FF-8B86-D011-B42D-00C04FC964FF). The unique identifier data type is commonly used as a primary key in a table when the application requires globally unique identifiers for records. It can also be used as a data type for columns that require unique values, such as in a table that stores user login information. The values in a unique identifier column are automatically generated by SQL Server, and the NEWID() function can be used to generate a new GUID value.

8. XML: The XML data type in SQL is used to store XML (Extensible Markup Language) data. XML is a widely used format for storing and exchanging data on the web. The XML data type is a variable-length binary data type that can store XML data up to 2GB in size. The XML data type can be used to store XML documents or fragments and can be queried and manipulated using various XML functions and methods provided by SQL. In addition, SQL provides various built-in functions and methods for parsing, querying, and manipulating XML data stored in the XML data type.

Best Practices to Choose the Right Data Type in SQL

Choosing the right data type in SQL depends on the nature and size of the data you want to store. Refer below the some best practices to help you choose the right data type for your SQL table-

1. Determine the nature of the data: Before choosing a data type, you need to understand the type of data you want to store. Is it text, numbers, or binary data? What is the expected size of the data? Answering these questions will help you narrow down the right data types for your table.
2. Choose the smallest data type possible: Using a data type that is larger than necessary can waste valuable disk space and affect query performance. Therefore, it is best to choose the smallest data type that can accommodate your data.
3. Consider future data growth: Your database may grow over time, and new data may require a different data type. Therefore, it is essential to choose a data type that can accommodate future data growth.
4. Avoid using generic data types: Generic data types such as VARCHAR and TEXT can store any type of data, but they are not optimized for specific data types. Therefore, it is best to use specific data types that are designed for the type of data you want to store.

What is a user-defined data type with examples?

A user-defined data type (UDT) is a custom data type created by the user to define the structure and characteristics of a new data type in SQL.UDT allows users to use multiple attributes in a single data type to make it easier to manage and use in the database.

To create a UDT, you have to use the ‘CREATE TYPE’ statement in SQL which can vary depending on the RDBMS. Let’s see an example of creating a UDT in an SQL Server –

Suppose you want to create a UDT name ‘zip’ to represent the pin code information of individuals

Syntax:

CREATE TYPE zip
FROM CHAR(5) NOT NULL

In the above example syntax, we have defined a new data type (UDT) called “zip” that consists of one attribute: “CHAR” (a CHAR with a maximum length of 50 characters). Now you can create a rule for this newly created UDT if required any rule or condition as given below, or you can define it directly with any columns of a table if no rule or condition is required –

Syntax:

CREATE RULE zip_rule
AS @number > 100 AND @number < 99951

In the above syntax, we have created a rule named ‘zip_rule’ which can store pin codes from 100 to 99951 only, it will throw an error while storing the data. The most important thing is that you have to bind the rule with the UDT to activate this rule otherwise new UDT will not follow the rule as given below –

Syntax:

EXEC sp_bindrule zip_rule, 'zip'

Now you can use this new UDT in any table as shown below –

Syntax:

CREATE TABLE Address(
City CHAR(25) NOT NULL,
Zip_code ZIP,
Street CHAR(30) NULL)

You can see the text of the rule using the below syntax –

Syntax:

EXEC sp_helptext zip_rule

You can drop (delete permanently) the Table, UDT or rule using the below syntax –

Syntax:

DROP TABLE Address
DROP TYPE Zip
DROP RULE Zip_rule

FAQs

Conclusion

Data types in SQL Server play an important role in managing and manipulating data tables. It is very important to choose the right data type for a column to optimize storage and performance. SQL Server provides various data types that can be used for different purposes, including numeric, character and string, date and time, binary, and other data types. We hope you would have liked this very well.

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