Ensure data integrity, security, and performance with every release through reliable database testing.
of critical business errors are linked to database issues
of data breaches involve direct database vulnerabilities
of major performance incidents stem from inefficient queries or schema design
of high-performing DevOps teams automate database testing as part of their deployment pipeline
Verify accuracy and consistency by checking every table, relation, and constraint for proper enforcement
Ensure every schema update and migration is error free and backward compatible
Quickly identify issues when data models or logic change, protecting against accidental data loss
Test query speed and efficiency under realistic data loads to prevent slowdowns and bottlenecks
Validate user roles and permissions and protect sensitive data with strict access policies
Confirm backups work and data can be restored without corruption in any situation
Check data is moved, transformed, and loaded accurately during upgrades and integrations
Simulate real-world business scenarios to guarantee data moves correctly through every step
Reliable data powers every modern business. Database testing is not just about finding bugs but about building trust in your systems and enabling confident decision making at every level. Teams that invest in data quality lay the groundwork for lasting success.
— Samay Thakkar, Founder and CEO
Discover how our expert database testing team combines comprehensive data validation with systematic testing methodologies to ensure data integrity, security, and performance. Click on each step to explore the details.
Analyze business logic and map out critical data flows
Create targeted test cases and establish secure, isolated test databases
Run integrity, performance, security, and regression tests across all environments
Log every issue with precise queries, error details, and context
Suggest schema or query improvements to boost speed and efficiency
Integrate database checks into every deployment and sprint
reduction in production data errors
faster recovery from backup scenarios
improvement in query performance after optimization
less time spent on compliance and audit preparation
