SQL Server 2025: REGEXP_LIKE() – Native Regular Expressions Arrive**

Introduction

SQL Server has never had true regular expression support built into the engine. Developers relied on:

• CLR functions
• LIKE hacks
• CHARINDEX
• XML PATH tricks
• External tools

That changes in SQL Server 2025 with the introduction of REGEXP_LIKE(), the first native RegEx function. It finally gives SQL Server the pattern-matching power found in Oracle, PostgreSQL, and MySQL.

Today we’ll look at how REGEXP_LIKE works, where it shines, how the optimizer handles it, and the exact patterns that SQL Server supports.

This is the foundation for the entire RegEx feature family coming in Days 7, 8, and 9.

What REGEXP_LIKE() Does

REGEXP_LIKE() checks whether a string matches a given regular expression pattern. It returns:

• 1 → match
• 0 → no match

Basic syntax:

REGEXP_LIKE(expression, pattern)

Example:

SELECT REGEXP_LIKE('Valhallan', 'hall') AS MatchResult;

Returns:

1

Supported Pattern Types

SQL Server 2025 uses a modern, Perl-compatible RegEx engine with support for:

• Literal matches
• Character classes: [a-z], [0-9]
• Anchors: ^, $
• Quantifiers: +, *, ?, {n}, {n,}
• Groups: (...)
• Alternation: a|b
• Escaped characters: \s, \d, \w, and more

Example: Match a gamer tag that ends with digits.

SELECT REGEXP_LIKE('Luke123', '^[A-Za-z]+[0-9]+$');

Case Sensitivity

RegEx is case sensitive unless you specify the i flag.

SELECT REGEXP_LIKE('VALHALLAN', 'valhallan', 'i');

Supported flags:

• i case-insensitive
• m multi-line
• s single-line
• x ignore whitespace

Example with flags:

SELECT REGEXP_LIKE('ValHallan', '^valh', 'i');

Advanced Examples

Here are real patterns you can use immediately.

1. Validate email format

SELECT *
FROM Users
WHERE REGEXP_LIKE(Email, ‘^[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+.[A-Za-z]{2,}$’);

2. Detect numeric-only gamer IDs

SELECT REGEXP_LIKE('5021', '^\d+$');

3. Validate a Fortnite player tag

Letters, digits, underscores:

SELECT REGEXP_LIKE('ProBuilder_21', '^[A-Za-z0-9_]+$');

4. Detect toxic messages

SELECT *
FROM ChatLog
WHERE REGEXP_LIKE(Message, '(idiot|trash|ez|noob)');

Great for moderation dashboards.

5. Extract meaningful log events

Find entries starting with timestamp format:

SELECT *
FROM Logs
WHERE REGEXP_LIKE(EventText, '^\d{4}-\d{2}-\d{2}');

Performance and Optimization

REGEXP_LIKE is a scalar function. It is not SARGable, so SQL Server cannot perform index seeks against it.

However, SQL Server 2025 optimizes RegEx evaluation internally:

• Compiled pattern cache
• Fast failure paths
• SIMD instructions for simple character classes
• Safe fallback to CPU-only regex engine

Best performance practices:

1. Use anchors

^pattern$ is much faster than pattern.

2. Avoid wide NVARCHAR(MAX) columns

Use VARCHAR(200–2000) when possible.

3. Pre-filter with LIKE

WHERE SomeColumn LIKE '%@%' 
AND REGEXP_LIKE(SomeColumn, '@[A-Za-z0-9.-]+\.');

4. Avoid unnecessary flags

Flags increase processing overhead.

Migration from Older RegEx Workarounds

Before SQL Server 2025, people used:

• LIKE '%pattern%' – not accurate
• PATINDEX – limited
• CLR Regex – required permissions
• External scripts in Python or PowerShell

Now you simply write:

REGEXP_LIKE(ColumnName, 'pattern')

Cleaner, faster, safer.

Common Mistakes

1. Misusing escape characters

Remember to double-escape in T-SQL:

SELECT REGEXP_LIKE('123', '\\d+');

2. Not using anchors

Example mistake:

REGEXP_LIKE('abc123', '\d')

This returns 1.
If you want only digits:

REGEXP_LIKE('abc123', '^\\d+$')

3. Using RegEx when LIKE is enough

If you only need simple wildcard matching, stick to LIKE.

Workshop: REGEXP_LIKE Playground

Step 1. Create test data

CREATE TABLE TestPatterns2025 (
    Id INT IDENTITY,
    Value VARCHAR(200)
);
INSERT INTO TestPatterns2025 (Value)
VALUES ('Luke123'),
       ('Pro_Editor'),
       ('Noob!'),
       ('Champion'),
       ('VALHALLAN2025');

Step 2. Match values ending with digits

SELECT *
FROM TestPatterns2025
WHERE REGEXP_LIKE(Value, '^[A-Za-z]+[0-9]+$');

Step 3. Match uppercase only

SELECT *
FROM TestPatterns2025
WHERE REGEXP_LIKE(Value, '^[A-Z]+$');

Step 4. Detect non-allowed characters

SELECT *
FROM TestPatterns2025
WHERE REGEXP_LIKE(Value, '[^A-Za-z0-9_]');

Step 5. Case-insensitive matching

SELECT *
FROM TestPatterns2025
WHERE REGEXP_LIKE(Value, '^val', 'i');

Step 6. Build a moderation filter

SELECT *
FROM TestPatterns2025
WHERE REGEXP_LIKE(Value, '(noob|trash|ez)', 'i');

Final Thoughts

REGEXP_LIKE is the gateway to full pattern matching in SQL Server. It replaces years of workarounds and gives developers an engine-level tool that pairs perfectly with API calls, JSON, and text-heavy workloads. In tomorrow’s article, Day 7, we expand this foundation with REGEXP_SUBSTR() and REGEXP_REPLACE(), which unlock substring extraction and transformation directly inside SQL.

References

• REGEXP_LIKE
https://learn.microsoft.com/sql/t-sql/functions/regexp-like-transact-sql

• Regular Expression Syntax
https://learn.microsoft.com/sql/t-sql/functions/regular-expression-reference

• SQL Server 2025 New Features
https://learn.microsoft.com/sql/sql-server/what-s-new-in-sql-server-2025