New era, new engine, and new names

Today is an exciting day for dbt Labs. In case you missed it, we held our annual dbt Launch Showcase at which we unveiled new capabilities for how developers, analysts, and organizations leverage the power of dbt. And as we rebuilt dbt's foundations with the new dbt Fusion engine, we saw an opportunity to refactor our naming to better align with the product as it now exists.

So: as part of today's launch, we're also announcing a series of name changes that reflect a more unified vision for dbt's end-to-end user experiences.

Let’s dig in.

A new engine for the future of dbt

By now you’ve likely heard of the dbt Fusion engine. If you missed it, check out the blog here. The dbt Fusion engine is a fundamental shift in how dbt understands and executes your code. It introduces three key new technological breakthroughs to dbt: lightning-fast performance, native SQL comprehension and state-awareness. A literal fusing together of the capabilities we acquired with SDF with everything you’ve known dbt to be to this point.

Fusion isn't just an engine—it's a glimpse of what's ahead. As data teams seek faster feedback loops, deeper runtime insights, and smarter automation, Fusion provides the foundation for this future. It’s the future of dbt and the thing that stitches it all together.

It’s all just dbt

In 2016, when dbt Labs (then Fishtown Analytics) was founded, I described dbt as “a command line tool that enables data analysts and engineers to transform data in their warehouses more effectively.” The product, for ~4 years, was very basic: a Python-based command-line tool that allowed users to take code from their local machine and deploy it into a data warehouse.

Needless to say, a lot has changed since then. Today’s dbt ecosystem includes:

• The all-new, all-Rust dbt Fusion engine.
• A widely-used suite of APIs powered by the dbt engine and metadata platform.
• A sophisticated identity and auth platform.
• A whole suite of products: 2 IDEs (local and web), a low-code editing experience, a data catalog, an orchestrator, a CI tool, a cost observability tool, a semantic layer, a tool for exploratory data analysis, an MCP server, and almost certainly more that I’m forgetting.
• An AI copilot experience that integrates with the entire platform.

Many of these experiences are local; others live in a remote server. That server can be in our cloud or it can be in yours. Some are OSS, some are source available, and some are proprietary. Some are free; some require a commercial license. All of them come together to form a single, integrated platform for data and analytics engineering.

We are moving towards having a single CLI that controls every bit of this functionality, from executing dbt run to reading metadata to adding a new user account.

This … is not the world of dbt in 2020, when our previous product names (dbt Core and dbt Cloud) were born. A very long way from it. The product experiences are new and the technology that underlies them is new.

I announced one of my main goals for the future of dbt at Coalesce 2024: One dbt. I had become hyper-frustrated with the separation between our Core and Cloud products; it didn’t make any sense and it didn’t help anyone. In my head, there was only a single product—dbt—and the failure was ours for not making that product work together in a cohesive fashion.

Today, we have taken significant technical steps to bring this vision to reality. The dbt Fusion engine sits at the heart of the dbt experience. It can be installed locally or used in the cloud. It can be used for free under a source available license, or it can be used under commercial terms. But wherever and however it runs, Fusion is Fusion.

The APIs, products, and AI experiences I listed before? They’re all built on top of Fusion. And they’re all a part of a single platform called, simply, dbt.

Associating product names with jobs to be done

If you haven’t noticed, we like boring names. The name “dbt” was originally short for “data build tool” which ended up becoming the name when none of the original committers could think of anything more creative.

Sometimes boring is good :)

As a part of our effort to clarify and unify our product naming, we’re going to stick with our history of straightforward, descriptive names:

• dbt Explorer is now…wait for it…dbt Catalog.
• Our drag-and-drop visual editing experience is dbt Canvas.
• dbt Insights is the new exploratory data analysis interface.
• Our web-based IDE is called dbt Studio.

These new names align with how data teams already think and—we hope!—will make it easier for you to describe the breadth of what dbt has to offer.

A new era for dbt - one product, choose your adventure

While these naming changes might seem subtle, they represent a fundamental shift in our vision for dbt. We're creating a more intuitive, integrated, and clear experience throughout.

• A single integrated platform: dbt
• Descriptive product names to better represent the roles they play in your workflow
• And with Fusion, the foundation for an exciting future ahead

Getting started is easier than ever. Download the VSCode extension and start experiencing Fusion first-hand. Build a model in Canvas and collaborate with your peers. Go wild.

It’s all dbt.