SQL is an essential skill for software testers working with database-driven applications. Whether you are testing an e-commerce platform, banking application, healthcare system, or customer relationship management solution, you may need to validate records, identify duplicate data, compare expected and actual results, and verify that transactions are stored correctly.<\/p>\n\n\n\n
Interviewers therefore use SQL questions to assess whether a tester can independently validate backend data instead of relying only on the application\u2019s user interface.<\/p>\n\n\n\n
This guide covers 20 commonly asked software testing SQL interview questions, with explanations and sample queries suitable for manual testers, automation testers, QA analysts, and software development engineers in test.<\/p>\n\n\n\n
\nNote:<\/strong> SQL syntax can vary slightly among MySQL, PostgreSQL, Oracle Database, Microsoft SQL Server, and other database management systems.<\/p>\n<\/blockquote>\n\n\n\n
Why Is SQL Important in Software Testing?<\/h2>\n\n\n\n
SQL enables software testers to:<\/p>\n\n\n\n
\n
- Validate data stored in database tables<\/li>\n\n\n\n
- Verify data inserted, updated, or deleted through the application<\/li>\n\n\n\n
- Test database procedures, triggers, and constraints<\/li>\n\n\n\n
- Identify duplicate, missing, or inconsistent records<\/li>\n\n\n\n
- Compare frontend values with backend data<\/li>\n\n\n\n
- Prepare test data for different scenarios<\/li>\n\n\n\n
- Validate data migrations and ETL processes<\/li>\n\n\n\n
- Investigate defects more efficiently<\/li>\n<\/ul>\n\n\n\n
A tester does not always need advanced database administration knowledge. However, a strong understanding of SQL queries, joins, aggregate functions, subqueries, and data integrity concepts can significantly improve testing effectiveness.<\/p>\n\n\n\n
Top 20 Software Testing SQL Interview Questions<\/h2>\n\n\n\n
1. What Is SQL, and Why Do Software Testers Use It?<\/h3>\n\n\n\n
SQL stands for Structured Query Language<\/strong>. It is used to create, retrieve, update, and manage data in relational databases.<\/p>\n\n\n\n
Software testers use SQL primarily to validate backend data. For example, when a customer creates an account through an application, a tester can query the relevant database table to confirm that the account information was stored correctly.<\/p>\n\n\n\n
SELECT *\nFROM customers\nWHERE email = 'testuser@example.com';<\/code><\/pre>\n\n\n\nThis query can help verify whether the expected customer record exists in the database.<\/p>\n\n\n\n
2. What Is Database Testing?<\/h3>\n\n\n\n
Database testing is the process of verifying the accuracy, integrity, consistency, security, and performance of data stored in a database.<\/p>\n\n\n\n
It may include testing:<\/p>\n\n\n\n
\n
- Tables and columns<\/li>\n\n\n\n
- Primary and foreign keys<\/li>\n\n\n\n
- Stored procedures<\/li>\n\n\n\n
- Views<\/li>\n\n\n\n
- Triggers<\/li>\n\n\n\n
- Constraints<\/li>\n\n\n\n
- Transactions<\/li>\n\n\n\n
- Data migrations<\/li>\n\n\n\n
- CRUD operations<\/li>\n\n\n\n
- Database security and access permissions<\/li>\n<\/ul>\n\n\n\n
For example, a tester may verify that submitting a registration form inserts exactly one record into the
users<\/code> table and that all mandatory fields contain valid values.<\/p>\n\n\n\n3. What Are DDL, DML, DQL, DCL, and TCL Commands?<\/h3>\n\n\n\n
SQL commands are commonly grouped according to their purpose.<\/p>\n\n\n\n
DDL: Data Definition Language<\/h4>\n\n\n\n
DDL commands define or modify database objects.<\/p>\n\n\n\n
Examples:<\/p>\n\n\n\n
CREATE TABLE
ALTER TABLE
DROP TABLE
TRUNCATE TABLE<\/pre>\n\n\n\nDML: Data Manipulation Language<\/h4>\n\n\n\n
DML commands modify table data.<\/p>\n\n\n\n
Examples:<\/p>\n\n\n\n
INSERT\nUPDATE\nDELETE<\/code><\/pre>\n\n\n\nDQL: Data Query Language<\/h4>\n\n\n\n
DQL retrieves data.<\/p>\n\n\n\n
SELECT\n<\/code><\/pre>\n\n\n\nDCL: Data Control Language<\/h4>\n\n\n\n
DCL manages database access.<\/p>\n\n\n\n
GRANT\nREVOKE\n<\/code><\/pre>\n\n\n\nTCL: Transaction Control Language<\/h4>\n\n\n\n
TCL manages database transactions.<\/p>\n\n\n\n
COMMIT\nROLLBACK\nSAVEPOINT\n<\/pre>\n\n\n\nTesters frequently use DQL commands for validation and DML commands for test-data preparation. DML operations should be performed carefully, especially in shared or production-like environments.<\/p>\n\n\n\n
4. What Is the Difference Between
DELETE<\/code>,TRUNCATE<\/code>, andDROP<\/code>?<\/h3>\n\n\n\n
Command<\/th> Purpose<\/th> WHERE Clause<\/th> Table Structure<\/th><\/tr><\/thead> DELETE<\/code><\/td>Removes selected or all rows<\/td> Yes<\/td> Retained<\/td><\/tr> TRUNCATE<\/code><\/td>Removes all rows<\/td> No<\/td> Retained<\/td><\/tr> DROP<\/code><\/td>Removes the entire table<\/td> No<\/td> Deleted<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n Examples:<\/p>\n\n\n\n
DELETE FROM employees
WHERE employee_id = 101;
TRUNCATE TABLE employees;
DROP TABLE employees;
<\/pre>\n\n\n\nIt is useful in a testing environment when specific test records must be removed.
TRUNCATE<\/code> andDROP<\/code> are more destructive and should only be executed with appropriate authorisation.<\/p>\n\n\n\n5. What Is a Primary Key?<\/h3>\n\n\n\n
A primary key is a column, or combination of columns, that uniquely identifies every row in a table.<\/p>\n\n\n\n
Primary-key values must be unique and cannot normally contain
NULL<\/code>.<\/p>\n\n\n\nCREATE TABLE customers (
customer_id INT PRIMARY KEY,
customer_name VARCHAR(100),
email VARCHAR(150)
);
<\/pre>\n\n\n\nA tester should verify that:<\/p>\n\n\n\n
\n
- Duplicate primary-key values are rejected<\/li>\n\n\n\n
- Null primary-key values are rejected<\/li>\n\n\n\n
- Each record can be uniquely identified<\/li>\n\n\n\n
- The application generates or assigns the key correctly<\/li>\n<\/ul>\n\n\n\n
6. What Is a Foreign Key?<\/h3>\n\n\n\n
A foreign key establishes a relationship between two tables. It references a primary key or unique key in another table.<\/p>\n\n\n\n
CREATE TABLE orders (
order_id INT PRIMARY KEY,
customer_id INT,
order_total DECIMAL(10, 2),
FOREIGN KEY (customer_id) REFERENCES customers(customer_id)
);<\/pre>\n\n\n\n\nThe foreign key ensures that an order cannot reference a customer who does not exist, unless the database design explicitly permits a null value.<\/code><\/pre>\n\n\n\nDuring testing, verify that:<\/p>\n\n\n\n
\n
- Valid referenced values are accepted<\/li>\n\n\n\n
- Invalid referenced values are rejected<\/li>\n\n\n\n
- Updates and deletions follow the configured referential rules<\/li>\n\n\n\n
- Orphan records are not created<\/li>\n<\/ul>\n\n\n\n
7. What Is the Difference Between a Primary Key and a Unique Key?<\/h3>\n\n\n\n
Primary Key<\/th> Unique Key<\/th><\/tr><\/thead> Uniquely identifies each row<\/td> Enforces uniqueness in a column or column combination<\/td><\/tr> Only one primary key is allowed per table<\/td> Multiple unique constraints may be allowed<\/td><\/tr> Does not normally allow NULL<\/code><\/td>Null handling varies by database system<\/td><\/tr> Commonly used for table relationships<\/td> Commonly used for values such as email addresses or usernames<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n For example,
customer_id<\/code> may be the primary key, whileemail<\/code> may have a unique constraint.<\/p>\n\n\n\nCREATE TABLE customers (
customer_id INT PRIMARY KEY,
email VARCHAR(150) UNIQUE
);<\/pre>\n\n\n\nA tester should verify both uniqueness rules independently.<\/p>\n\n\n\n
8. How Do You Find Duplicate Records in a Table?<\/h3>\n\n\n\n
Use
GROUP BY<\/code> with theHAVING<\/code> clause.<\/p>\n\n\n\nSELECT email, COUNT(*) AS occurrence_count
FROM customers
GROUP BY email
HAVING COUNT(*) > 1;
<\/pre>\n\n\n\nThis query returns email addresses that appear more than once.<\/p>\n\n\n\n
Duplicate detection is particularly useful when testing:<\/p>\n\n\n\n
\n
- User registration<\/li>\n\n\n\n
- Payment processing<\/li>\n\n\n\n
- Data migration<\/li>\n\n\n\n
- Batch imports<\/li>\n\n\n\n
- Form resubmission<\/li>\n\n\n\n
- Retry mechanisms<\/li>\n\n\n\n
- API idempotency<\/li>\n<\/ul>\n\n\n\n
For duplicates based on multiple columns:<\/p>\n\n\n\n
SELECT first_name, last_name, date_of_birth, COUNT(*) AS occurrence_count
FROM customers
GROUP BY first_name, last_name, date_of_birth
HAVING COUNT(*) > 1;
<\/pre>\n\n\n\n9. How Do You Find the Second-Highest Salary?<\/h3>\n\n\n\n
One common solution uses a subquery:<\/p>\n\n\n\n
SELECT MAX(salary) AS second_highest_salary
FROM employees
WHERE salary < (
SELECT MAX(salary)
FROM employees
);
Another approach uses DENSE_RANK():
SELECT salary
FROM (
SELECT
salary,
DENSE_RANK() OVER (ORDER BY salary DESC) AS salary_rank
FROM employees
) ranked_salaries
WHERE salary_rank = 2;<\/pre>\n\n\n\nis useful when multiple employees have the same salary because it ranks distinct salary values without skipping the next rank.<\/code><\/pre>\n\n\n\n10. What Is the Difference Between
WHERE<\/code> andHAVING<\/code>?<\/h3>\n\n\n\n
WHERE<\/code> filters individual rows before grouping.HAVING<\/code> filters grouped results after aggregate calculations.<\/p>\n\n\n\nSELECT *
FROM employees
WHERE department = 'Quality Assurance';
The above query filters individual employee records.
SELECT department, COUNT(*) AS employee_count
FROM employees
GROUP BY department
HAVING COUNT(*) > 10;
<\/pre>\n\n\n\nThe second query returns only departments containing more than 10 employees.<\/p>\n\n\n\n
In general:<\/p>\n\n\n\n
\n
- Use
WHERE<\/code> for row-level conditions<\/li>\n\n\n\n- Use
HAVING<\/code> for conditions involving aggregate results<\/li>\n<\/ul>\n\n\n\n11. What Are SQL Joins?<\/h3>\n\n\n\n
Joins combine related data from two or more tables.<\/p>\n\n\n\n
Assume the following tables:<\/p>\n\n\n\n
\n
customers<\/code><\/li>\n\n\n\norders<\/code><\/li>\n<\/ul>\n\n\n\nINNER JOIN<\/h4>\n\n\n\n
Returns records with matching values in both tables.<\/p>\n\n\n\n
SELECT<\/p>\n\n\n\n
c.customer_id,
c.customer_name,
o.order_id
FROM customers c
INNER JOIN orders o
ON c.customer_id = o.customer_id;
<\/pre>\n\n\n\nLEFT JOIN<\/h4>\n\n\n\n
Returns all records from the left table and matching records from the right table.<\/p>\n\n\n\n
SELECT\n c.customer_id,\n c.customer_name,\n o.order_id\nFROM customers c\nLEFT JOIN orders o\n ON c.customer_id = o.customer_id;\n<\/pre>\n\n\n\nRIGHT JOIN<\/h4>\n\n\n\n
Returns all records from the right table and matching records from the left table. Support for
RIGHT JOIN<\/code> depends on the database system.<\/p>\n\n\n\nFULL OUTER JOIN<\/h4>\n\n\n\n
Returns matching and nonmatching records from both tables. Support and syntax vary by database system.<\/p>\n\n\n\n
Joins are valuable in testing when a business transaction spans several tables.<\/p>\n\n\n\n
12. How Do You Find Customers Who Have Not Placed Any Orders?<\/h3>\n\n\n\n
Use a
LEFT JOIN<\/code> and check for a null value in the joined table.<\/p>\n\n\n\nSELECT\n c.customer_id,\n c.customer_name\nFROM customers c\nLEFT JOIN orders o\n ON c.customer_id = o.customer_id\nWHERE o.order_id IS NULL;\n<\/pre>\n\n\n\nThe same requirement can also be tested with
NOT EXISTS<\/code>:<\/p>\n\n\n\nSELECT\n c.customer_id,\n c.customer_name\nFROM customers c\nWHERE NOT EXISTS (\n SELECT 1\n FROM orders o\n WHERE o.customer_id = c.customer_id\n);\n<\/pre>\n\n\n\n
NOT EXISTS<\/code> is often clear and reliable for checking the absence of related records.<\/p>\n\n\n\n13. What Is a Subquery?<\/h3>\n\n\n\n
A subquery is a query nested inside another SQL query.<\/p>\n\n\n\n
Example:<\/p>\n\n\n\n
SELECT employee_id, employee_name, salary\nFROM employees\nWHERE salary > (\n SELECT AVG(salary)\n FROM employees\n);\n<\/p>\n\n\n\n
The inner query calculates the average salary. The outer query returns employees whose salaries exceed that average.<\/p>\n\n\n\n
Testers may use subqueries to:<\/p>\n\n\n\n
\n
- Compare records against calculated values<\/li>\n\n\n\n
- Find missing relationships<\/li>\n\n\n\n
- Validate data across tables<\/li>\n\n\n\n
- Isolate records that meet complex conditions<\/li>\n<\/ul>\n\n\n\n
14. What Is the Difference Between
UNION<\/code> andUNION ALL<\/code>?<\/h3>\n\n\n\nBoth operators combine the results of two or more
SELECT<\/code> statements.<\/p>\n\n\n\n\n
UNION<\/code> removes duplicate rows<\/li>\n\n\n\nUNION ALL<\/code> retains duplicate rows<\/li>\n<\/ul>\n\n\n\nSELECT email FROM current_customers\nUNION\nSELECT email FROM archived_customers;\n<\/code><\/pre>\n\n\n\nSELECT email FROM current_customers\nUNION ALL\nSELECT email FROM archived_customers;\n<\/code><\/pre>\n\n\n\nThe queries being combined must return compatible columns in the same order.<\/p>\n\n\n\n
From a testing perspective, use
UNION ALL<\/code> when duplicate occurrences are meaningful and must not be hidden.<\/p>\n\n\n\n15. How Do You Handle
NULL<\/code> Values in SQL?<\/h3>\n\n\n\n
NULL<\/code> represents a missing, unknown, or unavailable value. It is not the same as zero or an empty string.<\/p>\n\n\n\nTo find null values:<\/p>\n\n\n\n
SELECT *\nFROM employees\nWHERE manager_id IS NULL;\n<\/pre>\n\n\n\nTo find non-null values:<\/p>\n\n\n\n
SELECT *\nFROM employees\nWHERE manager_id IS NOT NULL;\n<\/pre>\n\n\n\nDo not use:<\/p>\n\n\n\n
WHERE manager_id = NULL\n<\/pre>\n\n\n\nComparisons with
NULL<\/code> requireIS NULL<\/code> orIS NOT NULL<\/code>.<\/p>\n\n\n\nYou can replace null values in query output using functions such as
COALESCE<\/code>:<\/p>\n\n\n\nSELECT\n employee_name,\n COALESCE(phone_number, 'Not Provided') AS phone_number\nFROM employees;\n<\/pre>\n\n\n\nThe exact null-handling functions available may vary by database.<\/p>\n\n\n\n
16. How Do You Validate Data Inserted Through an Application?<\/h3>\n\n\n\n
A tester can follow these steps:<\/p>\n\n\n\n
\n
- Record the input data submitted through the application.<\/li>\n\n\n\n
- Identify the database table affected by the transaction.<\/li>\n\n\n\n
- Use a unique value, such as an ID or email address, to retrieve the inserted record.<\/li>\n\n\n\n
- Compare each stored value with the expected result.<\/li>\n\n\n\n
- Verify default values, timestamps, status fields, and generated identifiers.<\/li>\n\n\n\n
- Confirm that related tables were updated correctly.<\/li>\n\n\n\n
- Check that duplicate or unintended records were not created.<\/li>\n<\/ol>\n\n\n\n
Example:<\/p>\n\n\n\n
SELECT\n customer_id,\n first_name,\n last_name,\n email,\n account_status,\n created_at\nFROM customers\nWHERE email = 'testuser@example.com';\n<\/pre>\n\n\n\nThe tester should validate both the visible user data and backend-generated fields.<\/p>\n\n\n\n
17. How Do You Validate an
UPDATE<\/code> Operation?<\/h3>\n\n\n\nFirst, capture the original data:<\/p>\n\n\n\n
SELECT customer_id, email, phone_number, updated_at\nFROM customers\nWHERE customer_id = 501;\n<\/code><\/pre>\n\n\n\nPerform the update through the application. Then execute the query again:<\/p>\n\n\n\n
SELECT customer_id, email, phone_number, updated_at\nFROM customers\nWHERE customer_id = 501;\n<\/code><\/pre>\n\n\n\nVerify that:<\/p>\n\n\n\n
\n
- The intended column was updated<\/li>\n\n\n\n
- Unrelated columns were not modified<\/li>\n\n\n\n
- The update affected the correct record<\/li>\n\n\n\n
- Audit fields were updated correctly<\/li>\n\n\n\n
- No duplicate record was inserted<\/li>\n\n\n\n
- Related tables remained consistent<\/li>\n\n\n\n
- The application displayed the updated data correctly<\/li>\n<\/ul>\n\n\n\n
For sensitive testing, the original values should be restored after execution when required by the test environment\u2019s data-management policy.<\/p>\n\n\n\n
18. How Do You Validate a
DELETE<\/code> Operation?<\/h3>\n\n\n\nBefore deletion, confirm that the target record exists:<\/p>\n\n\n\n
SELECT *\nFROM customers\nWHERE customer_id = 501;\n<\/pre>\n\n\n\nPerform the delete action through the application and query the record again:<\/p>\n\n\n\n
SELECT *\nFROM customers\nWHERE customer_id = 501;\n<\/pre>\n\n\n\nThe expected result depends on the application\u2019s deletion strategy.<\/p>\n\n\n\n
Hard Delete<\/h4>\n\n\n\n
The record is physically removed from the table.<\/p>\n\n\n\n
Soft Delete<\/h4>\n\n\n\n
The record remains in the table, but a status or flag changes.<\/p>\n\n\n\n
SELECT customer_id, is_deleted, deleted_at\nFROM customers\nWHERE customer_id = 501;\n<\/pre>\n\n\n\nA tester should also verify:<\/p>\n\n\n\n
\n
- Child-record behavior<\/li>\n\n\n\n
- Referential integrity<\/li>\n\n\n\n
- Audit logs<\/li>\n\n\n\n
- User permissions<\/li>\n\n\n\n
- Search-result visibility<\/li>\n\n\n\n
- Recovery or restoration behavior<\/li>\n\n\n\n
- Whether deleted records remain accessible through APIs<\/li>\n<\/ul>\n\n\n\n
19. What Are Transactions,
COMMIT<\/code>, andROLLBACK<\/code>?<\/h3>\n\n\n\nA transaction is a group of database operations treated as one logical unit.<\/p>\n\n\n\n
COMMIT<\/code> permanently saves the transaction:<\/p>\n\n\n\nUPDATE accounts\nSET balance = balance - 100\nWHERE account_id = 1;\n\nUPDATE accounts\nSET balance = balance + 100\nWHERE account_id = 2;\n\nCOMMIT;\n<\/pre>\n\n\n\n
ROLLBACK<\/code> reverses uncommitted changes:<\/p>\n\n\n\nUPDATE accounts\nSET balance = balance - 100\nWHERE account_id = 1;\n\nROLLBACK;\n<\/pre>\n\n\n\nTransaction testing is critical in financial, inventory, reservation, and order-processing systems. A tester should confirm that either all related operations succeed or all are reversed when a failure occurs.<\/p>\n\n\n\n
This behavior is associated with transaction atomicity: a transaction should not leave the database in a partially updated state.<\/p>\n\n\n\n
20. How Do You Test a Stored Procedure?<\/h3>\n\n\n\n
A stored procedure contains SQL logic stored and executed in the database.<\/p>\n\n\n\n
A systematic stored-procedure test should cover:<\/p>\n\n\n\n
\n
- Valid input parameters<\/li>\n\n\n\n
- Invalid input parameters<\/li>\n\n\n\n
- Null inputs<\/li>\n\n\n\n
- Minimum and maximum boundary values<\/li>\n\n\n\n
- Empty values<\/li>\n\n\n\n
- Output parameters<\/li>\n\n\n\n
- Expected result sets<\/li>\n\n\n\n
- Insert, update, and delete effects<\/li>\n\n\n\n
- Exception handling<\/li>\n\n\n\n
- Transaction rollback<\/li>\n\n\n\n
- Performance with large data volumes<\/li>\n\n\n\n
- User permissions<\/li>\n<\/ul>\n\n\n\n
A generic execution example is:<\/p>\n\n\n\n
CALL GetCustomerOrders(501);\n<\/code><\/pre>\n\n\n\nThe syntax may differ by database platform.<\/p>\n\n\n\n
After executing the procedure, validate its output and any database changes:<\/p>\n\n\n\n
SELECT *\nFROM orders\nWHERE customer_id = 501;\n<\/code><\/pre>\n\n\n\nDo not validate only the returned success message. Verify the actual records affected by the procedure.<\/p>\n\n\n\n
Additional SQL Queries Software Testers Should Practice<\/h2>\n\n\n\n
Find the Total Number of Records<\/h3>\n\n\n\n
SELECT COUNT(*) AS total_customers\nFROM customers;\n<\/pre>\n\n\n\nFind Records Created Today<\/h3>\n\n\n\n
SELECT *\nFROM customers\nWHERE created_at >= CURRENT_DATE\n AND created_at < CURRENT_DATE + INTERVAL '1 day';\n<\/pre>\n\n\n\nDate syntax differs among database systems, so use the appropriate functions for the platform being tested.<\/p>\n\n\n\n
Find the Highest Order Amount<\/h3>\n\n\n\n
SELECT MAX(order_total) AS highest_order_total\nFROM orders;\n<\/pre>\n\n\n\nCalculate the Average Order Amount<\/h3>\n\n\n\n
SELECT AVG(order_total) AS average_order_total\nFROM orders;\n<\/pre>\n\n\n\nFind the Number of Orders for Each Customer<\/h3>\n\n\n\n
SELECT
customer_id,
COUNT(*) AS order_count
FROM orders
GROUP BY customer_id;
<\/pre>\n\n\n\nRetrieve the Latest Five Orders<\/h3>\n\n\n\n
SELECT *\nFROM orders\nORDER BY order_date DESC\nFETCH FIRST 5 ROWS ONLY;\n<\/pre>\n\n\n\n