Snowflake’s Big Move to Boost Data Migration with New Acquisition
301Snowflake is making a bold move to improve its data migration tools by acquiring a startup called Datometry. The deal is for an undisclosed amount and aims to strengthen SnowConvert AI, one of Snowflake’s key tools for helping companies shift their data warehouses to the cloud more easily.
SnowConvert AI, which is free for users, was launched earlier this year. It uses Snowflake’s Cortex AI Agents to automate the process of converting and validating code during migration. The goal is to make moving data workloads less complicated and faster. Snowflake also offers another product called Snowpark Migration Accelerator, which specifically handles migrating Spark workloads. Both tools tackle common migration issues like mismatched schemas, incompatible code, data corruption, and workflow disruptions. Usually, companies have to manually test to ensure their logic and transformations are correctly translated to a new platform. Snowflake’s new acquisition aims to streamline this process even further.
How Datometry’s Tech Fits Into Snowflake’s Plans
The main reason Snowflake bought Datometry is to integrate its technology into SnowConvert AI. This will help speed up migrations and make them more reliable. A key piece of Datometry’s portfolio is Hyper-Q, a virtualization platform that allows applications designed for older data warehouses to run on modern cloud systems without rewriting SQL code. This means businesses can preserve their existing applications while moving to the cloud, saving time and effort.
Experts see Hyper-Q as a valuable addition. Charlie Dai, a vice president at Forrester, explains that Hyper-Q’s ability to emulate SQL statements and translate data in real-time complements SnowConvert AI’s static code conversion. While SnowConvert AI is good at converting code ahead of time, Hyper-Q handles dynamic, real-time translation for application-embedded SQL and other constructs that static converters might miss. This combined approach could make migrations smoother and more comprehensive.
What This Means for Snowflake and Its Competitors
The acquisition could give Snowflake an edge over rivals like AWS Redshift, Google BigQuery, and Azure Synapse. These competitors typically rely on traditional ETL processes and batch migrations, which can be slow and costly. Migration is a big decision for companies, especially when moving legacy systems like Oracle or Teradata. CFOs and CTOs worry about the costs, risks, and downtime involved.
By offering a faster and cheaper way to migrate—potentially for free—Snowflake is positioning itself as a more attractive option. Pareekh Jain, an analyst at Jain Consulting, says this could help Snowflake stand out. He notes that the ability to quickly and affordably migrate large warehouses is a major selling point. Making the process easier and less risky could sway more companies toward Snowflake’s platform.
Meanwhile, Snowflake’s main rival, Databricks, offers a similar AI-driven migration tool, thanks to its recent acquisition of BladeBridge. Databricks’ solution provides insights into migration scope, code transformation, and validation. However, it doesn’t currently have a virtualization platform like Hyper-Q, which could be a key differentiator for Snowflake.
In sum, Snowflake’s move to bring Datometry into its fold shows its commitment to making cloud data migration faster, easier, and more reliable. This could set a new standard in how enterprises transition their data warehouses to the cloud, helping Snowflake stay ahead in a competitive market.
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