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description: A consultant lays out how he advises enterprise clients choosing between two paths inside Snowflake's AIM (AI-driven Modernization and Virtualization)...
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# Virtualize First or Modernize First? How I Actually Advise Clients on Snowflake AIM

**[Snowflake Community](https://daily.dev/sources/snowflake_comm)** · 7 min read · 0 upvotes · 0 comments

## Summary

A consultant lays out how he advises enterprise clients choosing between two paths inside Snowflake's AIM (AI-driven Modernization and Virtualization) offering: virtualizing an existing Teradata estate to keep applications unchanged while running on Snowflake underneath, or fully modernizing by converting code, tables, and pipelines to run natively on Snowflake. Virtualization suits tight renewal deadlines, deeply coupled legacy applications, or risk-averse regulated industries, offering zero-downtime cutovers. Modernization suits teams wanting a fully native Snowflake environment with dbt pipelines and Snowpark-converted Spark workloads, at the cost of a rewrite. The piece argues the two approaches are not mutually exclusive and are often run in parallel, with virtualization as a first move and modernization following workload by workload.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://medium.com/snowflake/virtualize-first-or-modernize-first-how-i-actually-advise-clients-on-snowflake-aim-8d93ca0b3913>

## Questions this post answers

### What is Snowflake AIM and what does it include?

Snowflake AIM stands for AI-driven Modernization and Virtualization, a platform that unifies three migration routes under one umbrella: Teradata virtualization, data warehouse migration for platforms beyond Teradata, and Spark workload modernization. It is powered by migration agents running inside Snowflake CoCo, replacing what were previously separate approaches to legacy platform migration.

_Teams planning a Snowflake migration can track platform capabilities like this one on daily.dev._

### Should I virtualize or fully modernize when migrating off Teradata to Snowflake?

Virtualization suits situations with a tight renewal deadline under twelve months, applications tightly coupled to Teradata-specific SQL, or regulated industries that cannot tolerate big-bang cutover risk, since it requires no rewrite and offers zero downtime. Modernization suits teams wanting a fully native Snowflake environment with dbt pipelines and Snowpark-converted code, and is often pursued as a second phase after virtualization relieves immediate pressure.

_Weighing migration strategies gets easier when you follow real-world data platform trade-offs on daily.dev._

### How does Snowflake AIM handle Spark workload modernization?

AIM analyzes Python, Java, or Scala-based Spark code to identify the APIs in use, checks compatibility against Snowpark and Snowpark Connect, and automatically generates the code conversion rather than requiring an engineering team to hand port the workload. Legacy ETL workflows are similarly translated automatically into dbt running inside Snowflake.

_daily.dev helps engineers stay current on tooling changes like automated Spark-to-Snowpark conversion._

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---

Tags: [#snowflake](https://daily.dev/tags/snowflake), [#data-warehouse](https://daily.dev/tags/data-warehouse)

[View this post on daily.dev](https://daily.dev/posts/virtualize-first-or-modernize-first-how-i-actually-advise-clients-on-snowflake-aim-ohsrjczjq)

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