SQL Regular Expression (REGEXP) Tester

Test regular expressions for use in SQL queries. Simulate REGEXP and LIKE operations with sample data to see matches before running queries in your database.

SQL Regular Expression Tester (REGEXP)

Test and generate SQL regular expression patterns

Database Type

Case Sensitive

Regular Expression Pattern

Test String

Common Patterns

SQL Regex Syntax by Database

MySQL: REGEXP or RLIKE
PostgreSQL: ~ (case-sensitive), ~* (case-insensitive)
SQL Server: PATINDEX or LIKE with wildcards
Oracle: REGEXP_LIKE

How It Works

This SQL regular expression tester lets you experiment with REGEXP and LIKE patterns against sample data before using them in production queries, helping you get the syntax right.

The testing process:

Sample data input: Enter or paste test data that represents the kind of strings you'll be matching in your database.
Pattern definition: Write your regular expression or LIKE pattern using SQL regex syntax for your database dialect.
Match simulation: The tool applies your pattern to the sample data, showing which rows would match in an actual query.
Pattern refinement: Adjust your regex based on results until you get the exact matches you need.

Regular expressions in SQL are powerful but tricky. Testing patterns beforehand prevents failed queries and ensures you're matching exactly what you intend.

When You'd Actually Use This

Email Validation Queries

Test regex patterns for finding valid or invalid email addresses in user data.

Phone Number Extraction

Build patterns that match various phone number formats stored inconsistently in your database.

Data Cleaning

Identify records with malformed data (bad dates, invalid codes, inconsistent formats) for cleanup.

Log Analysis

Create patterns to extract specific information from log entries stored in database tables.

Product Code Matching

Test patterns for complex SKU or product code formats with specific structure requirements.

Learning SQL Regex

Experiment with regex syntax to understand how different patterns work in SQL context.

What to Know Before Using

Regex syntax varies between databases

MySQL uses REGEXP, PostgreSQL uses ~ and ~*, SQL Server uses LIKE with wildcards. Patterns may need adjustment for different databases.

Performance can be poor on large tables

Regex matching is CPU-intensive and often can't use indexes. Use for targeted queries, not full-table scans on millions of rows.

Case sensitivity matters

Some databases have case-sensitive regex (PostgreSQL ~) and case-insensitive variants (~*). MySQL REGEXP is case-insensitive by default for text columns.

Special characters need escaping

Characters like ., *, +, ?, [, ] have special meaning in regex. Escape them with backslash when you want literal matches.

NULL values don't match

REGEXP operations on NULL columns return NULL (unknown), not true or false. Use IS NULL checks separately if needed.

Common Questions

What's the difference between LIKE and REGEXP?

LIKE uses simple wildcards (% for any characters, _ for single character). REGEXP supports full regular expressions with character classes, quantifiers, and alternation. REGEXP is more powerful but slower.

How do I match the start or end of a string?

Use ^ for start of string and $ for end. Example: '^A' matches strings starting with A, 'z$' matches strings ending with z.

Can I use regex in WHERE and HAVING clauses?

Yes. REGEXP works anywhere you can use a boolean expression: WHERE, HAVING, CASE statements, and even in SELECT for conditional logic.

What regex features are supported in SQL?

Basic features (character classes, quantifiers, alternation) are widely supported. Advanced features (lookahead, backreferences) vary by database. Check your database documentation.

How do I match digits or letters specifically?

Use character classes: [0-9] or \d for digits, [a-zA-Z] for letters, [[:alpha:]] for alphabetic characters (POSIX syntax in some databases).

Why is my regex query so slow?

Regex can't typically use indexes, forcing full table scans. Consider adding a computed column with extracted values, or use LIKE for simple prefix matches.

Can I extract matched portions, not just test for matches?

Some databases support REGEXP_SUBSTR or SUBSTRING with regex to extract matched portions. MySQL 8+ and PostgreSQL have good regex extraction functions.

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