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title REGEXP_LIKE (Transact-SQL)
description REGEXP_LIKE Returns a Boolean value that indicates whether the text input matches the regex pattern.
author MikeRayMSFT
ms.author mikeray
ms.reviewer abhtiwar, wiassaf, randolphwest
ms.date 10/25/2025
ms.service sql
ms.subservice t-sql
ms.topic reference
ms.custom
build-2025
dev_langs
TSQL
monikerRange =sql-server-ver17 || =sql-server-linux-ver17 || =azuresqldb-current || =azuresqldb-mi-current || =fabric

REGEXP_LIKE (Transact-SQL) preview

[!INCLUDE sqlserver2025-asdb-asmi-fabric]

[!INCLUDE preview]

Indicates if the regular expression pattern matches in a string.

REGEXP_LIKE
     (
      string_expression,
      pattern_expression [, flags ]
     )

REGEXP_LIKE requires database compatibility level 170 and above. If the database compatibility level is lower than 170, REGEXP_LIKE isn't available. Other regular expression scalar functions are available at all compatibility levels.

You can check compatibility level in the sys.databases view or in database properties. You can change the compatibility level of a database with the following command:

ALTER DATABASE [DatabaseName] SET COMPATIBILITY_LEVEL = 170;

Note

Regular expressions are available in Azure SQL Managed Instance with the SQL Server 2025 or Always-up-to-date update policy.

Arguments

string_expression

[!INCLUDE regexp-string-expression]

pattern_expression

[!INCLUDE regexp-pattern-expression]

flags

[!INCLUDE regexp-flags-expression]

Return value

Boolean value. true or false.

Remarks

Cardinality estimation

To enhance the accuracy of cardinality estimation for the REGEXP_LIKE function, you can use the ASSUME_FIXED_MIN_SELECTIVITY_FOR_REGEXP and ASSUME_FIXED_MAX_SELECTIVITY_FOR_REGEXP query hints to adjust the default selectivity values. For more information, see Query hints.

These query hints are also integrated with Cardinality estimation (CE) feedback. The CE feedback model automatically identifies queries using REGEXP_LIKE function where there's a significant difference between estimated and actual row counts. It then applies the appropriate selectivity hint at the query level to improve plan quality without requiring manual input.

To disable the automatic feedback behavior, enable trace flag 16268.

Examples

Select all records from the Employees table where the first name starts with A and ends with Y

SELECT *
FROM Employees
WHERE REGEXP_LIKE (FIRST_NAME, '^A.*Y$');

Select all records from the Orders table where the order date is in February 2020:

SELECT *
FROM Orders
WHERE REGEXP_LIKE (ORDER_DATE, '2020-02-\d\d');

Select all records from the Products table where the product name contains at least three consecutive vowels:

SELECT *
FROM Products
WHERE REGEXP_LIKE (PRODUCT_NAME, '[AEIOU]{3,}');

Create employees table with CHECK constraints for Email and Phone_Number columns:

DROP TABLE IF EXISTS Employees;
CREATE TABLE Employees
(
    ID INT IDENTITY (101, 1),
    [Name] VARCHAR (150),
    Email VARCHAR (320)
        CHECK (REGEXP_LIKE (Email, '^[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Za-z]{2,}$')),
    Phone_Number NVARCHAR (20)
        CHECK (REGEXP_LIKE (Phone_Number, '^(\d{3})-(\d{3})-(\d{4})$'))
);

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