dbt, turbocharged

Meet the dbt Fusion engine. All new. Lightning fast.

The dbt you know and love — now way faster and more efficient.

Get started with FusionSee what's new
Why Fusion matters

Embrace the future of analytics.

Fusion is the next-generation dbt engine. Built on Rust and equipped with deep SQL comprehension, Fusion powers dbt Studio IDE, Canvas, and our new VS Code extension.

Build faster

Enjoy a hyper-responsive and intelligent developer experience

Optimize costs

Avoid unnecessary model runs by validating code before hitting the warehouse

Strengthen governance

Gain precise column-level awareness to support PII, PHI, and AI compliance

See what’s possible with Fusion

Built for speed and efficiency

From instant feedback to local compilation, Fusion redefines what’s possible with dbt. Experience the future of analytics engineering in action.

Bar chart comparing parse times for a 10,000-model project, showing a 30x improvement in speed when using dbt Cloud with Fusion versus dbt Core.
Unmatched performance

From minutes to milliseconds.

Fusion understands your SQL and validates it locally. Paired with the high-performing Rust language means parsing even the largest projects up to 30x faster.

A hyper-responsive coding environment, wherever you build.

Native SQL comprehension means a smarter, faster developer experience that keeps you in your flow. With Fusion, go from idea to insight in record time.

Intelligent SQL autocompletion & suggestions
Screenshot of dbt’s SQL editor showing auto-completion for the ref function, suggesting models like stg_customers, stg_orders, and stg_payments during query writing.
Built-in efficiency

Slash your warehouse compute costs.

Fusion emulates your cloud data platform locally, validating your analytics code as you write it—no need to execute unnecessary models or queries to spot an error. What’s more: State-aware orchestration only runs models when there’s new data upstream, allowing you to save ~10% on your data warehouse bill.

Local validation: Gain precise, real-time error feedback without hitting your data warehouse

State-aware orchestration: Reduce redundant runs by intelligently limiting builds to models with new upstream data

Column-aware CI: Avoid unnecessary costs by only building models if columns have been impacted (coming soon)

Data lineage diagram showing state-aware orchestration in dbt, where only new data in raw.orders triggers updates to downstream models like stg_orders, int_customer_orders, and fct_orders.

We anticipate the dbt Fusion engine will mark a new chapter for our data team — one where speed and efficiency are baked into every part of the analytics lifecycle.

Matt Karan Senior Data Engineer @Obie Insurance

Data lineage diagram showing how personally identifiable information (PII), like email and customer name, is governed and tracked across dbt models from stg_customers to fct_orders.
Precision governance

Govern sensitive data with confidence.

Fusion's deep SQL understanding will soon enable precise, column-level lineage and metadata management, essential for handling sensitive information such as PII or PHI.

Enhanced metadata tracking at column-level granularity

Robust lineage visualizations for compliance use-cases

Automated sensitive data detection and flagging

Trusted by high-performing teams

Faster builds. Smarter data. Happier teams.

From banks to airlines, early adopters are already shipping better data faster with Fusion under the hood.

Read customer stories
  • Nasdaq

    Before, 9 out 10 times the sales and executive team had to wait months to receive a data point they requested. By then, the data wasn’t relevant anymore or the new business was already lost.

    Michael Weiss, Senior Product Manager

    Read Nasdaq's story
  • Siemens

    Already in our first dbt Cloud project we were amazed by the seamless collaboration dbt Cloud offers, allowing us to effortlessly work together on the same Snowflake project. With built-in tests, simple job scheduling, and easy deployment, dbt Cloud enabled us to immediately focus on the business case rather than spending time on our data architecture setup.

    Rebecca Funk, IT Business Partner

    Read Siemens's story
  • Enpal

    We used to have outages on a regular basis where the organization wouldn’t have updated data for a whole day. This year, we’ve only had three or four minor hiccups that we could fix in a few hours.

    Alexander Novikov, Director of Data and BI

    Read Enpal's story
    Get started

    Try Fusion now. Experience the difference.

    Experience dbt's powerful new engine—built for speed, built for scale, built for you.

    Book a demo
    Start your trial