Soft Delete

Lesson content

Soft Delete Soft Delete is a practical SQL concept used to design, query, secure, operate, or analyze relational data correctly. Example UPDATE users SET deleted_at = CURRENT_TIMESTAMP WHERE id = 42; Key point Use the smallest correct statement, test it with representative data, and verify constraints and performance before production use. Real-life example An inventory service receives a confirmed business action and must change only the intended rows while preserving an audit-friendly history. Advanced example BEGIN; -- Preview the exact target set first. SELECT id FROM orders WHERE status = 'pending'; -- Apply the Soft Delete operation, verify affected rows, then commit. COMMIT; Expected result The schema or operation satisfies the stated rule, rejects invalid data, and can be verified with a repeatable query. Production check Test with empty, duplicate, null, and boundary values. Use a transaction for related writes. Inspect the execution plan before adding an index. Use parameterized queries for application input. Continue with the PicoStore database This lesson reuses picostore . Relevant tables: customers, products, orders, order_items . Keep the starter rows from the Introduction lesson so results remain comparable. Another practical example DELETE FROM orders WHERE status = 'cancelled' AND ordered_at < '2025-01-01'; SELECT COUNT(*) FROM orders WHERE status = 'cancelled'; Check the result Run the verification query, compare the returned rows with the starter data, and explain why every included or excluded row is correct. Easy example Start with a small customer table and retrieve active customers in a predictable order. SELECT customer_id, name, email FROM customers WHERE status = 'active' ORDER BY name; How to verify the easy example Run it with representative input. Confirm the expected output. Try one missing, invalid, or boundary value. Advanced example Use a CTE and a window function to rank customer revenue while keeping the query readable and testable. WITH customer_revenue AS ( SELECT customer_id, SUM(total_amount) AS revenue FROM orders WHERE order_status = 'completed' GROUP BY customer_id ) SELECT customer_id, revenue, DENSE_RANK() OVER (ORDER BY revenue DESC) AS revenue_rank FROM customer_revenue ORDER BY revenue_rank, customer_id; Advanced review Explain the tradeoffs and assumptions. Test failure, scale, security, and recovery behavior. Capture evidence from tests, execution plans, logs, or review output. Additional practical guidance Soft Delete: MySQL and PostgreSQL Preview the target rows and use a transaction for important changes. MySQL and PostgreSQL share the core statement, while RETURNING support, safe-update settings, and DDL transaction behavior may differ. Required verification Run the simple case. Test a NULL, duplicate, empty, or boundary case where relevant. Confirm the affected rows or query result. Use EXPLAIN for performance-sensitive queries.