Data migrations are rarely simple. Between legacy platforms, complex procedural logic and tight timelines, many teams struggle to move quickly without introducing risk. That’s exactly why we continue to invest in SnowConvert AI — to help make migrations to Snowflake easier with increased automation and to improve efficiency and reliability.
This quarter brings some of the most meaningful enhancements yet. Whether you’ve used SnowConvert AI before or are just getting started, now is a great time to (re)discover how it can accelerate your migration journey.
SnowConvert AI is a free, AI-powered migration solution that helps organizations migrate their complete data ecosystem to Snowflake — including data warehouses, ETL pipelines and business intelligence workloads. AI-powered capabilities are enabled through a Snowflake connection and leverage Snowflake Cortex AI for intelligent code conversion and validation.
SnowConvert AI combines automated code conversion, built-in testing and guided migration workflows to reduce manual effort, shorten migration timelines and help teams modernize while managing migration complexity.
SnowConvert AI supports automated SQL and procedural code conversion across a broad set of source platforms, including Oracle, Microsoft SQL Server, Teradata, Amazon Redshift, Google BigQuery, Greenplum, Sybase, Synapse, Netezza, PostgreSQL and Databricks SQL.
Conversions cover everything from tables and views to complex stored procedures and user-defined functions (UDFs). For Amazon Redshift and Microsoft SQL Server, SnowConvert AI also delivers a comprehensive end-to-end migration workflow — spanning schema and code conversion, data migration and validation — so teams can move faster and with greater confidence.
SnowConvert AI is also available through a unified command-line interface (CLI), designed for teams that need to integrate migrations into automated workflows, CI/CD pipelines and partner tooling.
The SnowConvert AI CLI enables end-to-end migrations from the command line — including code extraction, conversion, AI-powered verification, deployment, data migration and validation — bringing the full capabilities of SnowConvert AI beyond the desktop experience. It is purpose built for headless execution, noninteractive runs and integration with modern developer and agentic tools.
This CLI-first approach makes it easier for partners, professional services teams and advanced users to standardize, automate and scale migrations to Snowflake.
Following a successful public preview, AI-Powered Code Conversion is now generally available (GA). This capability uses SnowConvert AI’s advanced AI agents to analyze and convert SQL and procedural code to improve conversion accuracy and reduce latency.
As part of this GA release, SnowConvert AI includes one-sided verification, where converted code is validated by executing it on Snowflake using synthetic test data. This helps identify syntax and logic issues early in the migration process — before deployment — reducing manual review and rework.
One-sided AI-powered verification is available across multiple supported source platforms.
SnowConvert AI also supports two-sided verification, an advanced validation approach that executes converted logic on both the source system and Snowflake using synthetic test data, then compares the results.
If discrepancies are detected, SnowConvert AI automatically invokes AI-powered code conversion to repair the logic and revalidate the results — providing additional confidence in validation results before deployment.
Two-sided, source-system verification is currently available for SQL Server migrations, with support for additional platforms planned in future releases.
SnowConvert AI now supports converting source platform tables (such as Teradata) directly into Snowflake managed Iceberg tables.
This new target option addresses enterprise requirements for open table formats while still benefiting from Snowflake managed performance, governance, reliability and security — making it easier to modernize without compromising architectural flexibility.
As Sybase IQ approaches end of life, many organizations face the challenge of migrating deeply embedded, business-critical procedural logic.
SnowConvert AI now supports Sybase stored procedures and UDFs, enabling teams to:
This addresses one of the hardest parts of any migration — and significantly shortens timelines.
SnowConvert AI can now convert SSIS (.dtsx) projects into native dbt projects on Snowflake, helping teams modernize legacy ETL pipelines.
The result is a shift from brittle, legacy ETL to version-controlled, testable and scalable data pipelines — without having to start from scratch.
SnowConvert AI continues to strengthen trust in migrated data with a multilevel validation framework:
Validates structural consistency between source and target:
Validates data completeness at scale:
Provides the highest level of fidelity:
To help teams work efficiently with large and complex data sets, SnowConvert AI now includes new helper commands:
These capabilities are currently available for SQL Server and Redshift migrations, with support for additional platforms planned in future releases.
SnowConvert AI is designed to automate the most time-consuming parts of migration — but we know teams are often lean and balancing competing priorities.
That’s why Snowflake offers multiple ways to get help:
Whether you’re just starting or reengaging after a previous attempt, help is readily available.
Ready to get started? Download SnowConvert AI and complete the quickstart.
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