dbt Cloud

Deep SQL awareness feature that automatically updates all downstream references when a model or column is renamed, with preview of proposed changes before commit.

A governance and metadata tool that leverages rich metadata and lineage information to improve data quality, trust, and governance for analytics and AI development.

The managed platform for dbt that provides orchestration, governance, testing, and scalable data transformation execution for analytics and AI initiatives.

An AI assistant that transforms data engineering workflows by automating routine tasks and enabling data engineers to focus on high-impact work. Integrates with dbt platform to enhance productivity.

A protocol server that enables any AI tool to discover, query, and execute dbt projects with a single connection. Provides AI agents and copilots direct access to structured, governed, version-controlled data without brittle APIs.

Provides AI systems with standardized semantic context, metrics, and business definitions enabling them to make decisions aligned with company-specific data governance and definitions.

A feature that automatically builds only changed models and skips unchanged ones, helping reduce warehouse compute costs through intelligent incremental processing.

A new engine powering dbt that brings stateful intelligence to data pipelines, enabling automatic incremental builds and deep SQL awareness for automatic refactoring of models and columns.

Native development extensions for popular IDEs including Cursor, Claude Code, Windsurf, VS Code, and dbt Studio, enabling local SQL development experience with dbt capabilities.

A live, interactive DAG visualization that shows data flow and transformations across dbt projects with column-level lineage tracing. Allows filtering by model type, materialization, or dependency.

An AI agent purpose-built for analytics engineering that helps data teams build and refactor data models within the dbt CLI and platform.