DATABASE TESTING | EVERYTHING YOU SHOULD KNOW ABOUT
Database Testing Summary
Database testing ensures data accuracy, integrity, and performance by validating the backend of an application. It involves several types:
Structural Testing: Verifies schema, tables, indexes, and constraints.
Data Integrity Testing: Ensures relationships, foreign keys, and default values are consistent.
Functional Testing: Tests stored procedures, triggers, and CRUD operations.
Performance Testing: Checks query execution times and optimizations.
Common test scenarios include data validations after insert/update/delete, verifying relationships, executing stored procedures, and checking edge cases like NULL/default values.
You can use tools like SQL Developer, pgAdmin, or MySQL Workbench for manual testing, and automate with JDBC + Java, SQLAlchemy + Python, or DbUnit. Assertions usually focus on matching row counts, validating column data, and ensuring query results are accurate.
For automation, integrate tests into CI/CD pipelines using tools like Jenkins, and optimize performance by analyzing queries with EXPLAIN PLAN or ANALYZE.