Databricks users, get ready to experience the new dbt Fusion engine

Exciting news from the Databricks Data + AI Summit in San Francisco as today we’re expanding access for the public beta of the dbt Fusion engine to teams using Databricks as their data platform. For customers familiar with dbt, this upgrade isn’t just an incremental improvement on the dbt Core engine—it’s a fundamental shift in speed, intelligence, and developer experience for anyone building with dbt in the lakehouse.

The dbt Fusion engine experience on Databricks

The dbt Fusion engine represents a new era of analytics engineering. Born from a complete ground-up rewrite of dbt in Rust, Fusion is designed for performance at scale, pairing blazing-fast execution with deep understanding of your analytics code. For Databricks users, this means:

• Significant performance gains: Project parsing and compilation is as much as 30x faster than with dbt Core, dramatically reducing turnaround time from code change to insight.
• Developer intelligence: Fusion’s native SQL comprehension provides real-time feedback and error checking as you write SQL, catching mistakes and providing suggestions instantly—without executing queries against your warehouse. This now precisely understands Databricks SQL and provides all the same benefits to this ecosystem.
• Cost control: Fusion’s “state-aware orchestration” understands what’s changed in your data and code, so only necessary models run—eliminating redundant workloads and helping organizations reduce cloud compute spending by 10% or more.
• Better governance (coming later this year): Precise column-level lineage and richer metadata will soon provide enhanced data governance, making it easier to manage risk, enforce policies, and lay the foundation for safe AI applications downstream.

For teams used to the original Python-based dbt Core engine, Fusion’s upgrade is a game-changer. It empowers analytics engineers to move faster, iterate with confidence, and focus more on business logic than debugging or firefighting performance issues.

Who benefits?

• Data engineers and analytics engineers running transformations at scale on Databricks will see dramatically reduced compile and parse times of dbt projects, lower cloud spend, and richer metadata for downstream consumers.
• Organizations requiring strict governance, auditability, or cross-platform flexibility gain robust lineage, improved cost management, and the freedom to scale beyond a single data warehouse.

This is especially valuable for companies orchestrating complex pipelines, handling sensitive data, or operating in hybrid/multi-cloud environments.

The new industry standard

dbt is regarded as the industry standard for AI on structured data. The Fusion engine, with deep SQL comprehension, will power the next generation of dbt use cases.

Following the public beta, the dbt Fusion engine will be available for Databricks users through dbt or the VS Code extension. If you’re a dbt managed customer, you can enable Fusion for your projects with just a few clicks. For those working with Databricks on-premises or in hybrid setups, Fusion is also available as a source-available package under the Elastic License v2 (ELv2). This gives organizations the flexibility to install, use, and put dbt Fusion into production locally.

For a premium developer experience—including features like state-aware orchestration, cost management dashboards, and enterprise governance—dbt unlocks Fusion’s full value.

With the Fusion engine now powering Databricks transformations, we are setting the new standard for scalable, intelligent, and cloud-agnostic analytics workflows. And of course, we're not done yet—look out for support for more data platforms and dbt projects in the coming weeks.

Ready to experience it? dbt Fusion is currently in Public Beta, but you can review the docs or check out a demo.

We’ll be hosting Fusion demos all week at the Databricks Data + AI Summit. If you’re attending the show, swing by our booth to grab some great swag and experience the new super-charged dbt.