#1 Data Migration Testing Automation Tool

★★★★★

5.0

Capterra

★★★★★

4.7/5

Why Risk Your Multi-Million Dollar Migration Project?

Migrate to any cloud or on-premise database with confidence. iceDQ automates end-to-end database migration testing with no sampling and no manual effort. Instantly validate schemas, row counts, and data migration reconciliation across any data source.

Trusted by Fortune 500 companies

Why Choose iceDQ?

End-to-end data migration testing automation designed for complex database migration projects.

Cross-Platform Migration Testing

Seamlessly connect and test data across on-premise systems and cloud platforms using iceDQ's 150+ prebuilt connectors - validating every migration from legacy databases to modern cloud targets.

Migration Validation and Reconciliation

iceDQ validates schemas, row counts, transformations, and attribute-level data across source and target systems, ensuring complete reconciliation before and after cutover.

Catch Migration Edge Cases

Design complex test scenarios to detect rare data mismatches, truncation errors, encoding issues, and edge cases that traditional sampling methods miss during migration.

CI/CD and DataOps Integration

Trigger automated migration regression testing in your CI/CD pipeline using API-first design and connect with tools like Jenkins, Git, and Azure DevOps.

Auto-Rule Generation for Migration Projects

Automatically generate migration validation rules across thousands of tables and columns to ensure full coverage with minimal manual setup - reducing rule creation from weeks to hours.

Reusable Migration Test Suites

Reuse migration test cases across Dev, QA, UAT, and production environments to standardize validation and accelerate regression testing cycles across projects.

Out-of-Box Checks

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

High-Performance, Scalable Testing

Achieve million-record-per-second 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 systems, 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 regression testing and enable end-to-end testing for DataOps

Benefits

See the transformation iceDQ delivers across real migration projects

Migration Objects Validated

3,000

↓

5,000

67% more coverage

Migration Test Automation Level

10% - 20%

↓

95%

~5x improvement

Migration Test Coverage

Less than 80%

↓

100%

Full coverage achieved

️

Migration Testing Timeline

24 Months

↓

5 Months

79% faster delivery

Migration Testing Team Size

10 People

↓

5 People

50% team reduction

Migration 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

Migration Data Validation

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 Migrate with Confidence?

Try it for yourself today

Book a Demo

Frequently Asked Questions

What types of database migrations can iceDQ validate?

iceDQ validates all major migration types including legacy-to-cloud, on-premise-to-cloud, database-to-database, and cloud-to-cloud migrations. It supports source and target systems including Oracle, SQL Server, Teradata, DB2, SAP, Snowflake, Redshift, BigQuery, Azure Synapse, and more - validating schemas, row counts, transformations, referential integrity, and data reconciliation at every stage of the migration lifecycle.

How does iceDQ handle schema and data validation during migration testing?

iceDQ performs full attribute-level comparison between source and target, checking every record - not just samples - for schema mismatches, missing rows, duplicate records, null violations, data type mismatches, and transformation errors. It generates detailed mismatch reports showing exactly which records failed and why, giving your team the evidence needed to resolve issues before cutover.

Can iceDQ test migrations across cloud and on-premises environments?

Yes. iceDQ supports on-premises, public cloud, private cloud, and hybrid environments with 150+ native connectors. It validates ETL pipelines connecting Oracle, SQL Server, Teradata, Snowflake, Redshift, BigQuery, Azure Synapse, SAP, flat files, APIs, and more - in any combination of source and target.

How does iceDQ support cutover validation and go-live readiness?

iceDQ runs a full source-to-target reconciliation immediately before and after cutover, confirming that 100% of records migrated correctly and no data was lost or corrupted in transit. It provides audit-ready reports documenting test coverage, pass rates, and any exceptions - giving your team and stakeholders confidence to sign off on go-live.

How quickly can iceDQ auto-generate migration validation rules?

iceDQ's AI-driven auto-rule generation scans source and target schemas and generates validation rules across thousands of tables and attributes in hours. Rules cover completeness, data types, referential integrity, transformation logic, duplicates, and reconciliation - and can be reviewed, refined, and reused across migration waves and environments.

How quickly can we deploy iceDQ for our migration testing project?

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 migration stack, builds initial test suites, and gets your team validating data fast.

Once the migration is complete, can iceDQ monitor the target environment in production?

Yes. iceDQ goes beyond migration testing - the same validation rules you build during testing can be deployed directly into production as continuous data monitoring jobs. This means your post-migration environment is monitored for data anomalies, SLA breaches, and pipeline failures in real time, ensuring data reliability long after go-live.