🚀 SQL Query Optimization in 2025: 7 Techniques for Faster Performance

#sql #mariadb #database #dataengineering

Struggling with slow SQL queries? Your database might be working harder than it needs to. Let's fix that! Here are 7 proven techniques to make your SQL queries faster and more efficient. ⚡
🔹 1. Avoid IN, Use a JOIN on a Virtual Table
🔴 Slow:

SELECT order_id FROM orders WHERE city IN ('Berlin', 'Paris', 'Rome');

🟢 Faster:

SELECT o.order_id FROM orders AS o
JOIN (VALUES ('Berlin'), ('Paris'), ('Rome')) AS v(city) ON o.city = v.city;

✅ Why? It helps PostgreSQL optimize index usage better than a long IN clause.
🔹 2. Use ANY(ARRAY[ ]) Instead of IN (PostgreSQL Only)

SELECT product_id FROM order_items WHERE product_id = ANY(ARRAY[101, 202, 303, 404]);

✅ Why? It short-circuits as soon as a match is found, reducing comparisons.
🔹 3. Replace Correlated Subqueries with a JOIN
🔴 Slow:

SELECT c.customer_id FROM customers c  
WHERE EXISTS (SELECT 1 FROM orders o WHERE o.customer_id = c.customer_id AND o.amount > 1000);

🟢 Faster:

SELECT DISTINCT c.customer_id FROM customers c  
JOIN orders o ON c.customer_id = o.customer_id WHERE o.amount > 1000;

📌 Final Tips for Faster SQL Queries
✅ Avoid SELECT * – Fetch only necessary columns.
✅ Use Indexes – Ensure your WHERE conditions use indexed columns.
✅ Avoid Functions in WHERE – Indexes can’t optimize conditions like LOWER(email) = 'test@example.com'.
✅ Use LIMIT – If you don’t need all rows, stop scanning early.
🔗 Full breakdown of SQL optimizations in my article: https://medium.datadriveninvestor.com/sql-query-optimization-in-2025-7-simple-techniques-for-faster-database-performance-cf6ec06596d0
💬 What’s your favorite SQL optimization trick? Share in the comments! 🚀