🔎 SQL IN Operator – Match Multiple Values with Clean Code

Want to match a column against multiple values without repeating OR conditions?
The SQL IN operator is your go-to solution for elegant filtering and clean queries.

📌 What is SQL IN?

The SQL IN operator allows you to specify multiple values in a WHERE clause. It returns rows where the column value matches any value in the list.

💡 It’s a shorter, more readable alternative to multiple OR conditions.

🧾 SQL IN Syntax

SELECT column1, column2, ...
FROM table_name
WHERE column_name IN (value1, value2, value3, ...);

✅ Returns all rows where column_name equals any of the values listed.

✅ Example: Filter by City

SELECT customer_name, city
FROM customers
WHERE city IN ('Mumbai', 'Delhi', 'Bangalore');

🔍 Returns customers located in Mumbai, Delhi, or Bangalore.

🚫 NOT IN Operator

To exclude specific values, use NOT IN:

SELECT employee_name, department
FROM employees
WHERE department NOT IN ('HR', 'Finance');

🔁 This returns employees who are not in HR or Finance.

🧠 Use IN with Numbers

SELECT product_name, price
FROM products
WHERE price IN (999, 1499, 1999);

📌 Selects products with specific price points.

📅 Use IN with Dates

SELECT order_id, order_date
FROM orders
WHERE order_date IN ('2024-01-01', '2024-05-01', '2024-08-15');

🎯 Filters orders placed on specific dates.

🌀 IN vs Multiple OR Conditions

-- Using OR
SELECT * FROM users
WHERE role = 'Admin' OR role = 'Editor' OR role = 'Viewer';

-- Cleaner with IN
SELECT * FROM users
WHERE role IN ('Admin', 'Editor', 'Viewer');

✅ The IN version is shorter, more readable, and easier to maintain.

⚠️ Best Practices & Tips

  • Use IN only when the list size is reasonable (e.g., < 1000 items).
  • Avoid using NOT IN with NULL values—use NOT EXISTS or LEFT JOIN instead.
  • Combine with AND, BETWEEN, or LIKE for powerful filters.

🧪 Practice Challenge

Task: Retrieve products that are available in either ‘Red’, ‘Blue’, or ‘Black’ color.

SELECT product_name, color
FROM products
WHERE color IN ('Red', 'Blue', 'Black');

📝 Final Thoughts

The SQL IN operator is:

✅ Shorter than using multiple OR conditions
✅ Easier to read and maintain
✅ Perfect for filtering by lists of values in real-world datasets

Start using IN in your queries to make them cleaner, faster, and easier to debug.