Data Landscape Modernization

Automated Database Migration Tools Benchmark Report

McKnight Consulting Group

January 2026

Executive Summary

Cloud database migrations are on the rise, and with them, the challenges and risks associated with these projects.

Getting conversions right is crucial, as errors or inefficiencies can lead to costly downtime, data corruption, and compromised business insights. End-to-end cloud migration tools, such as Impetus’ LeapLogic, Databricks Lakebridge, Snowflake’s SnowConvert AI, and AWS’s Database Migration Service/Schema Conversion Tool (DMS/SCT), promise to streamline and simplify the migration process. However, not all tools are created equal; some tools go beyond database migration and have the ability to migrate other critical elements, including ETL, orchestration, and analytical and BI tools. Further, the quality of their conversions and breadth of their capabilities can vary significantly.

This benchmark report provides an in-depth evaluation of these leading automated database modernization migration tools, assessing their accuracy, efficiency, and reliability in converting complex database schemas and code. By comparing the strengths and weaknesses of each solution, this report aims to help organizations make informed decisions about their data estate migration strategies and ensure a successful transition to their target environment.

Our testing consisted of a multi-step process designed to evaluate the effectiveness of automated database migration tools. We began by selecting representative SQL, ETL, and BI artifacts, which served as the foundation for our testing. Next, we established manual-conversion baselines through timing and practitioner feedback, providing a reference point for comparison. We then executed automated conversions using designated tool-target pairs, followed by validation of each artifact's functional correctness post-conversion.

Throughout the process, we recorded key metrics, including conversion accuracy, conversion time, manual-effort savings, and migration project total timeline. To provide a more comprehensive understanding of the tools' performance, we extrapolated our findings to small, medium, and large migration project scenarios to represent what organizations might encounter in the real world. Finally, we aggregated the total project effort composition to model the full migration lifecycle.

We found that Impetus LeapLogic had capability and performance advantages across several key metrics when compared to competing solutions Lakebridge, AWS SCT, and SnowConvert AI. LeapLogic consistently demonstrates superior conversion accuracy and has a significant impact on reducing manual conversion work, showing efficiency gains that are close to 100% when compared to Lakebridge and 71% when compared to AWS SCT across various project sizes.

Tools Evaluated

Impetus LeapLogic (tested v5.1)

LeapLogic is an automated data and analytics workload modernization tool that supports the migration of SQL, ETL, and BI artifacts to modern cloud-based environments, including AWS, Azure, and Google Cloud. It supports a comprehensive collection of targets including Amazon Redshift, Aurora, Glue, and Snowflake Datawarehouse. The tool provides a range of features, including conversion engines and support for various database, ETL, BI, analytics, and mainframe platforms. LeapLogic is designed to facilitate workload migration.

Databrick’s Lakebridge (tested v0.10.12)

Lakebridge is a migration tool specifically designed for migrating data and workloads to Databricks. While it claims to have ETL migration support, we observed failures in converting Informatica ETL jobs.

Snowflake SnowConvert AI (tested SQL Conversion Core: v31.0.118)

SnowConvert AI automates the conversion of database code, including stored procedures and SQL scripts, to Snowflake's SQL dialect. It supports migrations from various database platforms.

AWS Database Migration Service (DMS) and Schema Conversion Tool (SCT) (tested v3.6.1)

DMS and SCT facilitate database migrations to Redshift on AWS. DMS provides a managed service for migrating databases, supporting both homogeneous and heterogeneous migrations, while SCT automates the conversion of database schema and code to AWS-compatible formats.

Migration Project Phases

When migrating databases, organizations typically follow structured phases: Assessment, Conversion, Validation & Testing, and Operationalization.

1. Assessment: Evaluate the current environment and determine migration risks.
2. Conversion: Convert the database schema, code, and other assets to the target platform's format.
3. Validation & Testing: Validate migrated assets for functionality and quality standards.
4. Operationalization: Deploy migrated assets and ensure they are properly configured.

By following these phases, organizations can ensure a successful migration project, minimize downtime, and realize the benefits of their target platform.

Migration Sizes

We categorize migration projects into three tiers based on scope, complexity, and impact:

• Small Migration: ~7,000 artifacts (legacy data warehouses of 3 to 9 TB).
• Medium Migration: ~20,000 artifacts (data volumes of 10 to 30 TB).
• Large Migration: ~45,000 artifacts (30 TB or more).

Benchmark Method

To assess accuracy, manual-effort reduction, and overall duration of migration tools, we designed a benchmark experiment using representative workloads consisting of SQL, ETL, and BI artifacts across multiple cloud data warehouse targets.

Results

Impetus LeapLogic vs AWS SCT

LeapLogic significantly reduces project time for migration compared to both manual efforts and AWS SCT. LeapLogic's performance in conversion accuracy and manual effort reduction showcases its efficiency.

Impetus LeapLogic vs Lakebridge

LeapLogic outperforms Lakebridge in conversion accuracy and manual effort reduction across various project sizes.

Impetus LeapLogic vs SnowConvert AI

LeapLogic demonstrates superior conversion accuracy and significantly reduces manual conversion work compared to SnowConvert AI.

Impetus LeapLogic Advantages

Assessment Phase

LeapLogic employs an automated assessment tool that forms the foundation of its modernization framework. It automatically inventories SQL, stored procedures, ETL mappings, and job scripts, evaluates technical debt, and maps dependencies.

Conversion Phase

LeapLogic’s high conversion accuracy is attributed to its pattern-based grammar translation engine.

Validation, Testing & Operationalization Phases

Validation with LeapLogic automates the certification of migrated workloads, ensuring data integrity, performance, and functional equivalence.

Conclusion

This benchmark report evaluated leading automated data workload migration tools, including Impetus LeapLogic, Databricks Lakebridge, Snowflake’s SnowConvert AI, and AWS DMS/SCT. The findings highlight that Impetus LeapLogic outperforms its competitors in conversion accuracy, efficiency gains, and broader support for ETL and orchestration, which positions it as a strong choice for organizations looking to modernize their data estate.