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Backticks or Square Brackets in SQL: Which to Use and Why?

Susan Sarandon
Release: 2024-12-29 12:58:15
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Backticks or Square Brackets in SQL: Which to Use and Why?

Backticks vs. Square Brackets in SQL Statements

In the realm of SQL, database professionals often need to use special characters to identify specific objects or keywords. Two commonly encountered characters in this regard are backticks and square brackets. Understanding their nuances can help ensure the clarity and compatibility of SQL statements.

Compatibility Considerations

SQL Server and T-SQL utilize square brackets to enclose identifiers, such as table or column names. MySQL, however, exclusively uses backticks for this purpose. Employing the incorrect character can lead to syntax errors or unexpected behaviors.

Backticks in MySQL

In MySQL, backticks () fulfill the dual role of enclosing identifiers and protecting them from being interpreted as reserved keywords. For instance, if a table has a column named "select," enclosing it in backticks (e.g., "select`") prevents conflict with the reserved SQL keyword "SELECT."

Square Brackets in SQL Server

In SQL Server, square brackets ([]) serve a similar function to backticks in MySQL. They encompass identifiers, allowing for the use of otherwise reserved keywords as object names. For example, a table could be named "[select]" to circumvent potential clashes with the "SELECT" keyword.

Additional Considerations

While backticks and square brackets generally serve the same purpose, it is crucial to use the appropriate character based on the database system being employed. Using backticks in SQL Server may result in syntax errors, and vice versa.

In Summary

When working with SQL, the use of backticks and square brackets is governed by the specific database system being used. MySQL demands the use of backticks for enclosing identifiers and protecting them from reserved keywords. Conversely, SQL Server requires square brackets to accomplish the same tasks. Understanding this distinction is essential for crafting clear, compatible, and error-free SQL statements.

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