Data Types in SQL Server: A Complete Guide to Choosing and Using Them

SQL Server data types are the foundation upon which your entire database structure rests. They define the kind of data you can store in each column, from simple integers and text strings to complex date/time values and binary data.

Picking the right SQL data type means your data is stored efficiently, queries run fast, and your information stays accurate. Using an overly large data type wastes space and slows things down, while using a too small type risks data loss or errors.

In this article, we’ll explore the most common SQL data types, covering the different categories with tips to help you choose the best fit for your database.

Table of contents

• Categories of SQL Server data types
• Choosing the right data type for your SQL Server database
• Using SQL Server data types in dbForge Studio for SQL Server
• Conclusion

Categories of SQL Server data types

We can broadly categorize data types in SQL into seven groups:

• Exact numeric: These store whole numbers and decimals with exact precision.
• Approximate numeric: These store fractional numbers where some degree of rounding or approximation is acceptable.
• Date and time: These types store date and time information.
• Character string: These handle your standard text data.
• Unicode character string: These store Unicode character data.
• Binary: These store binary data, such as images, documents, or other files.
• Special data types: These include unique identifiers, XML data types, and spatial data types that don’t neatly fit into the other categories.

Exact numeric data types

SQL exact numeric data types include integers, decimals, and money values. Each type has a different capacity, both in terms of value range and memory usage.

Take a look at the table below to see the details:

Approximate numeric data types

There are two approximate numeric data types: FLOAT and REAL. 

The SQL FLOAT data type is handy for representing extremely large or small numbers. It uses scientific notation to do it, and you can control the precision, which affects its accuracy. 

If you need a smaller floating-point type to save storage and are working with numbers within a more limited range, use the SQL REAL data type instead.

Date and time data types

The date and time data types include the following: 

• DATE:  It stores only the date. For example, a person’s birthdate, like 1990-03-09.
• TIME: It stores only the time of day (e.g., 14:30:00).
• DATETIME: It stores both date and time. Use it for things that don’t need millisecond precision, like storing transaction times and scheduling database backups.
• DATETIME2:  Like DATETIME, this type holds both date and time values. However,  it’s best for when you need higher precision, like logging system events or recording sensor readings.
• DATETIMEOFFSET: It stores the date and time, plus a time zone offset. This is essential if you need to track times specific to a location, like server logs from different regions (e.g., 2024-03-08 15:00:00 -07:00). Note this type is exclusive to SQL Server. While some databases offer similar functionality, MySQL data types lack a direct equivalent.

Character string data types

The character data type in SQL includes CHAR, VARCHAR, and TEXT. 

CHAR is for strings that are always the same length (n). Think codes and IDs. If you declare a column as CHAR(15), it will always use 15 characters worth of storage. If your text is shorter, it’ll pad it with spaces.

VARCHAR, on the other hand, is for strings that have varying lengths, so storage adjusts to the actual text size. For large blocks of text like articles and documents, use VARCHAR(MAX). It offers better performance and flexibility for large text fields compared to the deprecated TEXT data type.

Unicode character string data types

Need to support multiple languages or non-English characters in your database? Unicode data types are the way to go. They’re similar to their ASCII counterparts, just with an “N” in front. The most common ones are NCHAR, which stores fixed-length Unicode character strings, and NVARCHAR, which holds variable-length strings.

Binary data types

The SQL binary data type uses binary data types to store raw data, like images, PDFs, Word docs, audio files, video clips, compiled code. BINARY(n) stores fixed-length binary files and data, but it’s almost never a good idea. Files are rarely fixed in size, and this type will pad any data shorter than n bytes with zeros, wasting space. 

It’s much more common to use VARBINARY(n). It stores variable-length binary data, such as user-uploaded images or application files, without unnecessary padding.

Additionally, the IMAGE data type, which was used historically for storing large binary files, is now deprecated. Instead of IMAGE, it’s recommended to use VARBINARY(MAX). It handles large files (up to 2 GB) without the limitations of the IMAGE data type.

Special data types

SQL Server data types cover just about any storage need. Here are a few more you’ll likely run into:

• BIT stores boolean values (0 or 1, true/false), perfect for simple yes/no flags like email opt-ins.
• UNIQUEIDENTIFIER stores globally unique 16-byte IDs (GUIDs), so it’s ideal for things like e-commerce order tracking.
• XML stores structured XML data, so you can use it to store and query hierarchical data like a product catalog in XML or configuration settings.
• SQL_VARIANT can store values of different data types in one column, and it’s recommended only if you’re working with highly dynamic or unstructured data.
• GEOGRAPHY stores geographic coordinate data, so it’s useful for location-based services like finding the nearest store
• GEOMETRY stores geometric shapes and spatial data, which is why it’s typically used in mapping applications or CAD systems.
• HIERARCHYID stores hierarchical data, like how employees are organized in a company.
• VECTOR stores vector embeddings, useful for AI and machine learning tasks. It’s still in preview though, so it might change.

Choosing the right data type for your SQL Server database

Selecting the right data types in SQL is absolutely essential to make your database lean, mean, and fast. Storage-wise, the golden rule is to start small to keep costs down. Use the smallest data type that can handle your data, now and in the future.

Also, unless you’re working with financial data where every decimal place is crucial, avoid high-precision types. They’ll just waste storage space and impact performance. 

Tips for numeric data

Numeric data types in SQL Server can be tricky. If you’re doing a lot of calculations with whole number operations, stick with INT unless you need a bigger range.

Now, if you need exact decimal precision, use DECIMAL or NUMERIC. And a quick word about currency: FLOAT is generally not recommended. It’s an approximate type, so you could end up with small but potentially significant inaccuracies in your calculations.

Tips for date and time data

DATETIME stores date and time, but with limited precision for fractional seconds. DATETIME2 bumps up that precision and handles a wider range of dates. 

If you’re dealing with data from different time zones, use DATETIMEOFFSET. It’s almost always best to store your date and time data in UTC, and convert to local time only when you’re displaying it to the user. Also, use a consistent date and time format when inserting or updating data to avoid ambiguity and conversion errors. 

Tips for string data

As a rule of thumb, fixed-length strings (CHAR, NCHAR) are really only useful if all your strings are the exact same length. For everything else, VARCHAR is your go-to. It’s efficient and only uses the space it needs. 

Need to support international characters? Use the Unicode types NCHAR and NVARCHAR, with NVARCHAR usually being the better choice because of its variable length. Just remember, NVARCHAR uses double the storage of VARCHAR, so only use it if you actually need Unicode support.

Check our article on when to Use CHAR, VARCHAR, and VARCHAR(MAX) in SQL to learn more about each one.

Using SQL Server data types in dbForge Studio for SQL Server

Data types in SQL can be a headache, especially in complex schemas. Managing them, plus conversions and data integrity, is a constant challenge.

dbForge Studio for SQL Server can simplify things. Its Database Designer lets you visually create and edit your schema, which gives you a much clearer picture of how data types impact everything. In the SQL editor, code completion and syntax highlighting speed up your writing, and the built-in validator catches errors as you type, preventing data type mismatches. 

You can also instantly jump to any object’s definition right from your code to check its type and keep things consistent.

Conclusion

Getting SQL Server data types right is essential for any database. The right choice affects everything: storage, performance, data integrity, even how well your application runs.  Visualizing your schema can be a huge help, letting you see how different choices, including data types, affect your database design.

dbForge Studio offers tools for this, plus streamlined SQL editing and performance monitoring. If you’re spending too much time with data types or worrying about database bottlenecks, try dbForge Studio for SQL Server.