Database Testing: SQL Queries Every QA Should Know (2025 Complete Guide)(All the highlighted lines are codes so that has to come in code boxes)
Picture this: You’re testing a new food delivery app. A customer places an order for pizza, but when they check their order history, it shows Chinese food instead. The payment went through, the restaurant received the wrong order, and the customer is frustrated. What went wrong? Most likely, a database issue that could have been caught with proper testing.
If you’re a college student stepping into the world of Quality Assurance or a professional looking to pivot into tech, understanding database testing isn’t just helpful—it’s your ticket to landing better QA roles with higher salaries.
Why Database Testing is Your Secret Weapon in QA
Database testing is like being a detective for data. While other testers focus on what users see on the screen, database testers dig deeper to ensure the information flowing behind the scenes is accurate, secure, and fast.
Here’s a reality check: According to a 2024 Stack Overflow survey, QA professionals with database skills earn 35% more than those without. Companies like Google, Microsoft, and Amazon specifically seek QA engineers who can write SQL queries and understand data flow.
But here’s the good news—you don’t need a computer science degree to master database testing. With the right approach and practice, anyone can learn these skills.
The Foundation: What Actually Happens in Database Testing?
Before diving into SQL queries, let’s understand what we’re testing. Every time you:
Multiple database operations happen in milliseconds. Database testing ensures these operations work correctly under normal conditions, edge cases, and even when thousands of users act simultaneously.
Think of a database as a digital filing cabinet. Database testing checks if:
Essential SQL Queries That Will Make You Stand Out
1. Data Validation Queries (The Bread and Butter)
Checking if Data Exists
— Did the user registration actually work?
SELECT COUNT(*) FROM users
WHERE email = ‘newuser@gmail.com’
AND created_date >= CURDATE();
Finding Data Problems
— Are there any orders with negative amounts? (This shouldn’t happen!)
SELECT order_id, customer_name, total_amount
FROM orders
WHERE total_amount < 0 OR total_amount IS NULL;
These queries are your first line of defense. After any application feature is tested, you verify the data landed correctly in the database.
2. Relationship Testing (Making Sure Everything Connects)
Finding Broken Links Between Tables
— Are there orders without valid customers? (Orphaned records)
SELECT o.order_id, o.customer_id
FROM orders o
LEFT JOIN customers c ON o.customer_id = c.customer_id
WHERE c.customer_id IS NULL;
Checking Data Consistency Across Tables
— Do all order items reference real products?
SELECT oi.order_item_id, oi.product_id
FROM order_items oi
LEFT JOIN products p ON oi.product_id = p.product_id
WHERE p.product_id IS NULL;
Real-world impact: These queries once helped a QA team at an e-commerce company discover that 15% of orders had invalid product references, causing checkout failures.
3. Performance and Load Testing Queries
Finding Duplicate Data (Performance Killer)
— Multiple accounts with same email? This slows down login!
SELECT email, COUNT(*) as duplicate_count
FROM users
GROUP BY email
HAVING COUNT(*) > 1;
Identifying Heavy Database Operations
— Which queries are taking too long?
SELECT query_text, execution_time, rows_affected
FROM query_performance_log
WHERE execution_time > 5000 — 5 seconds
ORDER BY execution_time DESC;
4. Business Logic Validation
E-commerce Example
— Are there products with impossible inventory?
SELECT product_name, stock_quantity, reserved_quantity
FROM products
WHERE stock_quantity < reserved_quantity;
Financial Application Example
— Account balances that don’t add up
SELECT account_id,
(SELECT SUM(amount) FROM transactions WHERE account_id = a.account_id) as calculated_balance,
current_balance,
current_balance – (SELECT SUM(amount) FROM transactions WHERE account_id = a.account_id) as difference
FROM accounts a
HAVING difference != 0;
5. Security Testing Queries
Checking for Sensitive Data Exposure
— Are passwords properly encrypted?
SELECT user_id, username, password
FROM users
WHERE LENGTH(password) < 20; — Encrypted passwords are usually longer
Access Control Validation
— Users with admin privileges (should be limited)
SELECT username, role, last_login
FROM users
WHERE role = ‘admin’
ORDER BY last_login DESC;
Real-World Testing Scenarios You’ll Encounter
Scenario 1: Testing User Registration
When testing Swiggy’s user signup:
sql
–– Verify new user was created with correct details
SELECT username, email, phone, is_verified, created_date
FROM users
WHERE email = ‘testuser@example.com’;
— Check if verification email record was created
SELECT * FROM email_queue
WHERE recipient_email = ‘testuser@example.com’
AND email_type = ‘verification’;
Scenario 2: Testing Payment Processing
For testing PhonePe or Paytm transactions:
sql
— Verify payment record creation
SELECT transaction_id, amount, status, created_time
FROM payments
WHERE user_id = 12345
ORDER BY created_time DESC;
— Check wallet balance update
SELECT balance_before, balance_after, transaction_amount
FROM wallet_history
WHERE transaction_id = ‘TXN123456’;
Scenario 3: Testing Data Migration
When apps update their database structure:
sql
— Compare data before and after migration
SELECT
(SELECT COUNT(*) FROM old_customer_table) as old_count,
(SELECT COUNT(*) FROM new_customer_table) as new_count,
(SELECT COUNT(*) FROM new_customer_table) – (SELECT COUNT(*) FROM old_customer_table) as difference;
Tools That Will Make Your Life Easier
Free Database Tools for Beginners:
Cloud-Based Options:
Pro Tips for Database Testing Success
Career Growth: Where Database Testing Takes You
Entry Level (0-2 years): ₹3-6 LPA
Mid Level (2-5 years): ₹6-12 LPA
Senior Level (5+ years): ₹12-25 LPA
Specialised Roles:
Industry Demand: The Numbers Don’t Lie
According to Naukri.com’s 2024 IT Skills Report, database testing skills appeared in:
Companies actively hiring QA professionals with database skills include Flipkart, Paytm, BYJU’S, Zomato, and hundreds of product startups across Bangalore, Hyderabad, and Pune.
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