10 SQL Anti-Patterns You Must Avoid in Production

10 SQL Anti-Patterns You Must Avoid in Production “Slow SQL isn’t always about bad servers — it’s often about bad habits.” As SQL developers and data engineers, we often prioritize functionality and overlook query quality. But poor SQL habits can lead to: Long response times Bottlenecked applications Excessive I/O and CPU Poor scalability In this post, we’ll break down 10 critical SQL anti-patterns and how to fix them. ❌ 1. N+1 Query Pattern Problem: Querying in a loop for each record. -- BAD: Fetching orders per customer inside loop SELECT * FROM Customers; -- For each customer: SELECT * FROM Orders WHERE customer_id = ?; ✅ Fix: Join and aggregate in one query SELECT c.id, c.name, COUNT(o.id) AS order_count FROM Customers c LEFT JOIN Orders o ON o.customer_id = c.id GROUP BY c.id, c.name; ❌ 2. Wildcard Index Scans Problem: Leading wildcard disables index usage. SELECT * FROM Products WHERE name LIKE '%phone'; ✅ Fix: Use full-text search or structured LIKE -- Better (index usable) SELECT * FROM Products WHERE name LIKE 'phone%'; ❌ 3. Implicit Data Type Conversions Problem: Filtering numeric column with a string. SELECT * FROM Orders WHERE id = '123'; ✅ Fix: Match types explicitly SELECT * FROM Orders WHERE id = 123;

May 12, 2025 - 23:11

“Slow SQL isn’t always about bad servers — it’s often about bad habits.”

As SQL developers and data engineers, we often prioritize functionality and overlook query quality. But poor SQL habits can lead to:

In this post, we’ll break down 10 critical SQL anti-patterns and how to fix them.

Problem: Querying in a loop for each record.

-- BAD: Fetching orders per customer inside loop
SELECT * FROM Customers;
-- For each customer:
SELECT * FROM Orders WHERE customer_id = ?;

✅ Fix: Join and aggregate in one query

SELECT c.id, c.name, COUNT(o.id) AS order_count
FROM Customers c
LEFT JOIN Orders o ON o.customer_id = c.id
GROUP BY c.id, c.name;

Problem: Leading wildcard disables index usage.

SELECT * FROM Products WHERE name LIKE '%phone';

✅ Fix: Use full-text search or structured LIKE

-- Better (index usable)
SELECT * FROM Products WHERE name LIKE 'phone%';

Problem: Filtering numeric column with a string.

SELECT * FROM Orders WHERE id = '123';

✅ Fix: Match types explicitly

SELECT * FROM Orders WHERE id = 123;