What’s New in dbt? Latest News and Updates

What Is dbt?

dbt, short for data build tool, is a platform for transforming data. It helps data teams turn raw data into useful datasets. dbt mainly handles the transformation stage of modern ELT workflows. dbt works with data stored in modern data warehouses. Teams use SQL or Python to define data models. dbt also supports testing, documentation, version control, and collaboration. These features help teams build reliable and maintainable data workflows.

What Is the Difference Between dbt v1 and dbt v2?

What Does dbt Do?

dbt helps teams transform raw data into clean, useful datasets. It focuses mainly on data transformation inside data platforms.

Teams use SQL or Python to create and manage data models. dbt also helps teams test their data and track code changes.

It can generate documentation and show how data moves between models. This makes data workflows easier to understand and maintain.

dbt also supports version control and collaboration through tools like Git. These features help teams manage data projects more consistently.

Which Data Platforms Does dbt Support?

dbt supports many popular cloud data platforms and warehouses. These include Snowflake, BigQuery, Databricks, Redshift, and DuckDB. dbt also supports ClickHouse and Spark with beta support. Other platforms include Microsoft Fabric, Postgres, and Amazon Athena.

Latest dbt News and Updates

dbt has introduced several updates across its products during 2026. These updates focus on performance, AI, and data development.

New dbt Features and Improvements

dbt introduced dbt v2, powered by its Rust-based Fusion engine. It aims to provide faster development and processing. dbt also introduced dbt State and dbt Charts.

dbt Core Updates

dbt Core v1.12 became generally available in August 2026. It added several developer improvements and new capabilities. These include UDF improvements and a new on_error setting. It also supports ad hoc SQL through dbt run-operation --sql.

dbt Cloud Updates

dbt Platform has added easier Fusion upgrades for eligible projects. Users can upgrade projects directly through the platform interface. dbt also added release tracks for managing update schedules.

dbt AI Updates

dbt has expanded its AI features with the dbt Developer Agent. The agent can understand dbt projects and help create changes. dbt also added AI integrations through its MCP server.

At dbt Summit 2026, dbt announced dbt Wizard and new AI integrations. These features help users work with dbt projects using AI tools.

What Is dbt State and When Should You Use It?

dbt State checks what changed before building your data models. It compares your model SQL with metadata from your data warehouse. Then, it builds only the models that need updating. It can also skip, clone, or defer models when appropriate.Use dbt State when your projects contain many models. It helps avoid rebuilding models that have not changed. This can reduce development time and unnecessary warehouse computing. dbt State works with self-hosted dbt and the dbt platform.

Major Changes in dbt

dbt has made several major changes across its engine and platform. These updates focus on speed, AI, and easier data development.

New Tools and Capabilities

dbt v2 now uses a Rust-based engine across the platform. It improves performance and provides faster development workflows. dbt also introduced dbt State, dbt Wizard, and dbt Charts.

Changes to Existing Features

dbt Core v1.12 added several improvements for existing workflows. These include UDF improvements, simpler configurations, and ad hoc SQL support. It also introduced an optional Rust-based parser for testing.

Updates for Data Teams

Data teams now have more tools for building and managing data projects. dbt State can reduce unnecessary model builds and warehouse computing. AI tools can also work with project context, lineage, tests, and documentation.

dbt Core vs dbt Platform: What’s the Difference?

dbt Core was the open-source version of dbt for local development. In 2026, dbt v1 remains available as the earlier Core version. dbt Platform is a managed service for building and running dbt projects. It provides web-based development, orchestration, collaboration, and other features. Today, dbt v2 provides a newer Rust-based engine for local development. The dbt Platform also uses this newer engine. This means users can work with the same modern engine. The main difference is how teams manage and run their projects.

How the Latest dbt Updates Affect Users

The latest dbt updates give users faster tools and improved development workflows. They also add new AI features for working with data projects. These changes can help teams manage data more efficiently.

Why dbt News Matters for Data Teams

Following dbt news helps teams understand new tools and workflow changes. Recent updates include dbt v2, dbt State, and new AI features.These changes can affect how teams build, test, and manage data projects. Staying updated also helps teams understand new options for their workflows.

How to Keep Up With dbt News

You can follow dbt’s official blog for the latest product news and updates. You can also check dbt’s release notes for version changes. Follow dbt’s official channels for important announcements and events. This helps you learn about new features and product changes quickly.

Frequently Asked Questions About dbt

What is dbt used for?

dbt helps data teams transform raw data into clean, useful datasets. It supports testing, documentation, and data workflow management.

Is dbt free to use?

Yes, dbt is available for free for local use. dbt OSS is also available under the Apache 2.0 license.

What is the latest version of dbt?

dbt v2 is now generally available as the latest major version. dbt Core v1.12 also remains available for existing users.

Where can I find official dbt news?

You can find official updates on the dbt product news blog. The dbt Developer Hub also provides release notes and developer updates.

Final Thoughts on dbt News

dbt continues to add new features for modern data teams. Recent updates include dbt v2, dbt State, and new AI tools. Staying updated helps users understand these changes and new capabilities. It also helps teams decide when new features fit their workflows.