Snowflake Turbocharges dbt with Fusion

Snowflake integrates dbt Fusion, boosting compilation speeds for complex projects with no added cost or reconfiguration required.

Daniel Singer

Editor, StartupHub.ai

May 19 at 7:02 PMUpdated Aug 22, 20263 min read

Illustration of dbt Fusion integrated with Snowflake platform interface — dbt Fusion is now available on Snowflake, enhancing data transformation performance.· Snowflake

Visual TL;DR

Complex dbt projectsDriver

increasingly complex data transformation pipelines require faster builds

From the article 8 mentionsdbt Fusion is designed to improve compilation speeds without requiring users to undertake complex migration overhead.

Snowflake dbt FusionCore

From the article 9+ mentionsSnowflake is rolling out dbt Fusion as a selectable version within its Snowflake dbt Projects offering.

Faster compilation speedsEffect

boosts compilation speeds for complex projects significantly

From the articledbt Fusion is designed to improve compilation speeds without requiring users to undertake complex migration overhead.

Simple version toggleContext

From the articleA simple version toggle within Snowflake Workspaces allows users to switch to Fusion without altering their project configurations.

Platform upgradesEffect

From the article 3 mentionsThis update is part of broader improvements to Snowflake's native dbt support, touching platform capabilities, developer experience, orchestration, and CI/CD pipelines.

Streamlined orchestrationEffect

improvements to CI/CD pipelines and orchestration

From the article 2 mentionsNative Snowflake Tasks can now execute dbt projects, integrating data transformation into existing Snowflake workload orchestration.

No extra costOutcome

no new pricing tiers or contract changes generally required

Contents(4)

Snowflake is rolling out dbt Fusion as a selectable version within its Snowflake dbt Projects offering. This move aims to accelerate compilation times, particularly for increasingly complex data transformation pipelines, according to the announcement.

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GitLab

$146M

Snowflake

$12.4B

A cloud-based data platform enabling data warehousing, data lakes, data engineering, and data sharing.

dbt Fusion is designed to improve compilation speeds without requiring users to undertake complex migration overhead. A simple version toggle within Snowflake Workspaces allows users to switch to Fusion without altering their project configurations.

This update is part of broader improvements to Snowflake's native dbt support, touching platform capabilities, developer experience, orchestration, and CI/CD pipelines.

Faster Compilations, No Extra Cost

The availability of dbt Fusion on Snowflake means faster builds, especially as project complexity grows. Existing users can access Fusion with no new pricing tiers or contract changes generally required.

Users can enable Fusion by creating a new project or migrating an existing one into Snowflake.

Platform and Developer Experience Upgrades

Snowflake Workspaces and deployed dbt project objects now support dbt Core versions 1.9.4, 1.10.15, and dbt Fusion 2.0.0-preview via Snowflake CLI 3.15.0.

Developer workflows are enhanced with options to build in integrated development environments (IDEs) or directly within the browser. Snowflake's Cortex Code integrates with VS Code and other IDEs, managing the full lifecycle of dbt CLI operations.

For those preferring a browser-based environment, Snowsight Workspaces offer a fully managed platform with pre-installed dbt versions and a built-in Cortex Code panel. This environment also supports column-level lineage via the Snowflake Horizon Catalog.

Snowflake meets developers where they work.

Streamlined Orchestration and CI/CD

Native Snowflake Tasks can now execute dbt projects, integrating data transformation into existing Snowflake workload orchestration. This includes support for task graphs, dependency management, and alerting.

For Airflow users, pipelines can be created to execute dbt project objects, with Cortex Code available for authoring and editing these pipelines.

Snowflake CLI remains the go-to for deploying and executing dbt projects in external CI/CD pipelines. Snowflake-managed network policies for GitHub are now generally available, simplifying authentication for GitHub Actions workflows.

Expanded CI/CD support for Azure DevOps and GitLab is in public preview, alongside GA support for multiversion switching via the --dbt-version flag.

Triggered actions in Snowsight allow users to initiate dbt workflows automatically upon pull requests or commits.

The company plans continued investment in dbt Core version cadence, expanded CI/CD integrations, and overall developer experience, aiming to make Snowflake the premier platform for building and running dbt projects without infrastructure management overhead.

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#dbt #Snowflake #Data Engineering #Cloud Data Warehousing #AI #Developer Tools #Data Transformation #Cortex Code

Written by

Daniel Singer

Editor, StartupHub.ai

Daniel Singer is the editor of StartupHub.ai, a technology expert and thought leader on AI and its applications across sectors, from fintech and healthcare to developer tooling and consumer software. He writes and tests the tools covered here thoroughly and regularly, and built StartupHub.ai to give founders, operators and buyers a clearer read on what they are actually being sold.