🔍 SQL LIKE Operator – Search with Wildcards Like a Pro

Want to filter data based on patterns instead of exact values?
The SQL LIKE operator helps you find text that matches a specific pattern, not just an exact match.

It’s perfect for partial searches, email filtering, name lookups, and more.

📌 What is SQL LIKE?

The SQL LIKE operator is used in a WHERE clause to search for a specified pattern in a column.

It is commonly used with:

  • % (percent) – represents zero, one, or many characters
  • _ (underscore) – represents a single character

🧾 SQL LIKE Syntax

SELECT column1, column2, ...
FROM table_name
WHERE column_name LIKE pattern;

Wildcard patterns:

PatternMeaning
'A%'Starts with A
'%Z'Ends with Z
'%ice%'Contains “ice”
'_at'Matches “cat”, “bat”, “hat”, etc.
'M___'Starts with M and is exactly 4 characters

✅ Example 1: Find Names That Start with ‘S’

SELECT first_name
FROM employees
WHERE first_name LIKE 'S%';

🧠 Matches: Sam, Steve, Shubham

✅ Example 2: Find Products Ending with “Pro”

SELECT product_name
FROM products
WHERE product_name LIKE '%Pro';

✅ Matches: iPhone Pro, Galaxy Pro, Surface Pro

✅ Example 3: Emails That Contain “edu”

SELECT email
FROM users
WHERE email LIKE '%edu%';

🎯 Finds all emails containing “edu” (e.g., .edu domains)

✅ Example 4: Match Exact Character Patterns

SELECT code
FROM coupons
WHERE code LIKE 'A_3';

🧩 This matches codes like “AB3”, “AC3”, but not “A33” or “A3”

🚫 Use NOT LIKE to Exclude Patterns

SELECT username
FROM users
WHERE username NOT LIKE 'admin%';

This query excludes usernames that begin with “admin”.

💡 Tips for Using LIKE

  • Use LOWER() or UPPER() for case-insensitive searches (some databases are case-sensitive by default). WHERE LOWER(name) LIKE 'john%'
  • Avoid leading % when possible – it’s less performant as it prevents index use.

🧪 Practice Challenge

Task: Find customer names that contain “raj” anywhere in the name.

SELECT customer_name
FROM customers
WHERE customer_name LIKE '%raj%';

📝 Final Thoughts

The LIKE operator is a must-have tool for:

✅ Flexible search queries
✅ Pattern-based filtering
✅ Dynamic user input search

Use it with wildcards (%, _) to perform powerful text searches—across names, emails, product codes, and more.