--- title: "Dynamic Tables Just Got Faster and Far More Flexible — PART 2" url: https://daily.dev/posts/dynamic-tables-just-got-faster-and-far-more-flexible-part-2-vhlaaaocj source_url: https://medium.com/snowflake/dynamic-tables-just-got-faster-and-far-more-flexible-part-2-3c1c3ce734c4 type: article source: "Snowflake Community" published: 2026-08-26T16:22:34.334Z updated: 2026-08-26T16:54:49.081Z tags: ["data-engineering", "snowflake", "apache-iceberg"] reading_time: 6 upvotes: 0 comments: 0 language: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Dynamic Tables Just Got Faster and Far More Flexible — PART 2 **[Snowflake Community](https://daily.dev/sources/snowflake_comm)** · 6 min read · 0 upvotes · 0 comments ## Summary A deep technical walkthrough of Snowflake's Dynamic Tables platform updates, covering DML support (DELETE/UPDATE/MERGE) within frozen regions, adaptive refresh mode (public preview) that lets Snowflake choose between incremental and full recompute, BACKFILL FROM for zero-copy migration of historical data into frozen regions, refresh boundaries (GA) enabling independent freshness schedules and a Dynamic Table → View → Dynamic Table pattern, storage lifecycle policies (GA) for declarative data retention, Apache Iceberg read/write support, and new dbt/Airflow orchestration options that let external schedulers replace TARGET_LAG. Every example was tested against a live Snowflake account, with exact SQL, error messages, and output states shown. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### Can I run DELETE or MERGE statements directly on a Snowflake Dynamic Table? Yes, but only on rows inside the table's frozen region. Running DELETE, UPDATE, or MERGE on rows within the mutable (non-frozen) region still fails, and on a Dynamic Table with no frozen region at all, the operation raises a SQL compilation error such as 'Invalid Operation MERGE on Dynamic Table'. This is because the non-frozen region is derived and would be overwritten on the next refresh. _See how frozen-region DML changes GDPR deletion and historical corrections on daily.dev._ ### What does REFRESH_MODE = ADAPTIVE do for a Snowflake Dynamic Table? Adaptive refresh mode, in public preview, lets Snowflake's heuristics choose between incremental processing and full reinitialization at each refresh based on which is cheaper at that moment. It guards against unexpectedly re-executing expensive functions like Cortex AI Functions or UDFs across full history, and creation fails proactively if the query definition cannot support incremental refresh at all. _Compare adaptive versus auto refresh trade-offs before picking a mode on daily.dev._ ### How does BACKFILL FROM let you migrate historical data into a Snowflake Dynamic Table without reprocessing it? BACKFILL FROM zero-copy clones existing historical data directly into a Dynamic Table's frozen region, avoiding a full recomputation of years of clean data. It requires a frozen region to be defined on the table, and the resulting table reports refresh_mode = INCREMENTAL, backfill_from set to the source table, and insert_only_inputs = true. Retrofitting frozen regions later still forces the recomputation you were trying to avoid. _Track pipeline migration features like this one for Snowflake on daily.dev._ ## Similar posts on daily.dev - [Dynamic Tables Just Got Faster and Far More Flexible — PART 1](https://daily.dev/posts/dynamic-tables-just-got-faster-and-far-more-flexible-part-1-vtotqxtfm) · Snowflake Community · 0 upvotes · 0 comments - [Dynamic Tables on Iceberg](https://daily.dev/posts/dynamic-tables-on-iceberg-fra29yj5e) · Snowflake Community · 0 upvotes · 0 comments - [Next-Gen Data Engineering: 6 Snowflake Features Transforming How You Build](https://daily.dev/posts/next-gen-data-engineering-6-snowflake-features-transforming-how-you-build-hzcf1bert) · Snowflake · 0 upvotes · 0 comments --- Tags: [#data-engineering](https://daily.dev/tags/data-engineering), [#snowflake](https://daily.dev/tags/snowflake), [#apache-iceberg](https://daily.dev/tags/apache-iceberg) [View this post on daily.dev](https://daily.dev/posts/dynamic-tables-just-got-faster-and-far-more-flexible-part-2-vhlaaaocj)