#1 Database Testing Automation Tool

★★★★★

5.0

Capterra

★★★★★

4.7/5

Database Reliability Starts with Automated Testing.

iceDQ automates database testing across Oracle, SQL Server, MySQL, PostgreSQL, Snowflake, Redshift, BigQuery, Azure Synapse, Teradata, DB2, SAP HANA, and more. It validates schemas, row counts, transformations, and referential integrity across billions of records with no sampling and no manual effort - ensuring full database reliability at every stage of your data lifecycle.

Trusted by Fortune 500 companies

Why Choose iceDQ?

End-to-end database testing automation designed for full-coverage validation across any database platform.

Test Any Database - Cloud or On-Premises

Connect and validate any database - Oracle, SQL Server, MySQL, PostgreSQL, Snowflake, Redshift, BigQuery, Azure Synapse, Teradata, DB2, SAP HANA, and more - using iceDQ's 150+ ready-to-use connectors across cloud and on-premise environments.

Database Integrity Testing and Reconciliation

iceDQ validates schemas, row counts, referential integrity, transformations, and business rules across source and target databases - catching integrity violations, orphaned records, and constraint failures before they reach production.

Catch Database Edge Cases and Corner Cases

Design complex test scenarios to detect rare data anomalies, constraint violations, encoding issues, and edge cases across billions of database records that traditional sampling methods and manual QA miss entirely.

CI/CD and DataOps Integration

Trigger automated database regression testing in your CI/CD pipeline using API-first design. Connect with Jenkins, Git, and Azure DevOps to catch schema changes and data integrity failures on every deployment - before they reach production.

AI-Driven Auto-Rule Generation

Automatically generate database validation rules across thousands of tables and columns in hours using iceDQ's AI rules engine - covering completeness, data types, referential integrity, duplicates, and business logic with minimal manual setup.

Reusable Database Test Suites

Reuse database test cases across Dev, QA, UAT, and production environments to standardize validation and accelerate regression testing cycles across every database release and schema change.

Out-of-Box Checks

Accelerate Database Testing with Prebuilt Data Reliability Checks

Custom

Complex conditions using custom expressions

Completeness

Validates for NULLs, spaces, or empty values

Contains

Verifies attribute contains only specified values

Datatype

Checks if value can be cast to a specific type

Range

Ensures values fall within a specified range

Date

Validates strings against selected date formats

Pattern

Matches values against a regular expression

Duplicate

Detects duplicates across one or more attributes

Length

Checks the length of each attribute value

Reconciliation

Cross-system record matching and validation

Features

Easy, Low-Code/No-Code Testing

Automate database test generation with minimal effort
Powerful scripting for complex database validation scenarios, with rule-based validation and reconciliation

High-Performance, Scalable Testing

Achieve million-record-per-second database testing speeds
Flexible deployment on-prem or in the cloud with parallel and cluster processing

Seamless Connectivity and Integration

Connect to over 150 databases, cloud platforms, and file sources
Integrate seamlessly with test case management and ticketing systems

Accelerate DataOps with API-First Design

Fully compatible with CI/CD pipelines
Automate database regression testing and enable end-to-end validation for DataOps

Benefits

See the transformation iceDQ delivers across real database testing projects

Database Objects Validated

3,000

↓

5,000

67% more coverage

Test Automation Level

10% - 20%

↓

95%

~5x improvement

Database Test Coverage

Less than 80%

↓

100%

Full coverage achieved

️

Testing Timeline

24 Months

↓

5 Months

79% faster delivery

Testing Team Size

10 People

↓

5 People

50% team reduction

Database Regression Cycles

3 Months

↓

1 Month

3x faster cycles

Trusted by Industry Leaders

We have standardized iceDQ for all our cloud migration.

Senior Director of Advanced Analytics, Albertsons

We probably saved 5,000 hours ($500,000) on the Data Migration Project.

Head of Quality Assurance,
PepsiCo

BMC was able to achieve 100% test coverage after iceDQ implementation.

Director of Business Analytics, BMC Software

RuleGen utility helped Pfizer reduce the duration of IT testing from 24 months to 2 months.

Head of Data Governance,
Pfizer

iceDQ has enabled testers to keep up with the pace of developers and reduced the testing time by half.

Director of Quality Assurance,
HealthFirst

Not only did we achieve near perfect quality, but we also saved time and money on the project.

Director of Quality Engineering, Cencora

Built-In Functionalities

Parameterization

Rules Wizard

Database Integrity Testing

Data Monitoring

Built-In Scheduler

️User-Defined Function

Flat File Testing

️SAP HANA Migration Testing

Reporting and Analytics

Security - LDAP and SSO

Query Designer

Regression Testing

Salesforce Migration Testing

Alerts and Notifications

️Integrated Key Vault

Ready to Ensure Complete Database Reliability?

Try it for yourself today

Book a Demo

Frequently Asked Questions

What types of databases can iceDQ test?

iceDQ automates testing across all major database platforms including Oracle, SQL Server, MySQL, PostgreSQL, Snowflake, Redshift, BigQuery, Azure Synapse, Teradata, DB2, SAP HANA, Databricks, and more. It supports on-premises, cloud, and hybrid environments with 150+ native connectors - validating schemas, row counts, referential integrity, transformations, and business rules across any combination of source and target database.

How does iceDQ validate database integrity at scale?

iceDQ uses an in-memory processing engine that validates 100% of records - not 5-10% samples - at million-record-per-second speeds. It performs full attribute-level comparison across source and target databases, detecting schema mismatches, missing records, referential integrity violations, duplicate rows, null violations, constraint failures, and transformation errors across billions of records in a single run.

What types of database tests can iceDQ automate?

iceDQ automates the full spectrum of database testing including schema validation, row count verification, referential integrity checks, constraint validation, duplicate detection, data type verification, null handling, transformation logic testing, cross-database reconciliation, and regression testing. It covers unit, functional, and integration testing for databases across Dev, QA, UAT, and production environments.

How does iceDQ support database regression testing in CI/CD pipelines?

iceDQ is built API-first with native integrations for Jenkins, Azure Pipelines, GitHub Actions, Bamboo, and Git. Database regression test suites run automatically on every schema change or deployment - catching integrity violations and transformation regressions before they reach production. Test results push directly to JIRA, Azure Test Plans, HP ALM, and ServiceNow for full traceability across your QA workflow.

How quickly can iceDQ auto-generate database validation rules?

iceDQ's AI-driven auto-rule generation scans source and target database schemas and generates validation rules across thousands of tables and columns in hours - work that would take a manual team weeks. Rules cover completeness, data types, referential integrity, business logic, duplicates, and reconciliation, and can be reviewed, refined, and reused across environments and database releases.

Can iceDQ monitor databases in production after testing is complete?

Yes. The same validation rules you build during database testing can be deployed directly into production as continuous data monitoring jobs. iceDQ monitors for schema drift, data anomalies, constraint violations, and SLA breaches in real time - alerting your team before bad data reaches downstream systems, applications, or business users.

How quickly can we deploy iceDQ for our database testing environment?

Most organizations complete a proof of concept within 2-4 weeks and full deployment within 30 days. Every iceDQ customer receives a dedicated Forward Deployed Engineer (FDE) for 3 months at no additional cost - who configures the platform to your specific database stack, builds initial test suites, and gets your team validating databases fast.