dbt Labs
dbt Labs helps data practitioners create and disseminate organizational knowledge. It pioneered analytics engineering and provides open-source and commercial tools for transforming, testing, documenting, governing, and sharing trusted, AI-ready data.
At a Glance
- Enterprise data teams
- Analytics engineers and data engineers
- Data analysts and business intelligence teams
- Data platform and governance teams
- +2 more
AI Tools by dbt Labs
(1)
dbt Charts
Dashboards as Code with YAML
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Latest News
dbt announced support for Amazon Redshift data sharing, positioning it as a faster pipeline workflow.
dbt Summit 2026 announcements: dbt v2 GA, dbt State GA, Lake Compute private beta, dbt Wizard public preview, and dbt Charts public beta.
dbt Labs launched a rearchitected global partner ecosystem program with Visionary, Advanced, and Registered tiers.
dbt Labs unveiled the Rust-based dbt Fusion engine, VS Code extension, MCP server, dbt Canvas, and dbt Insights.
Products & Services
Open-source command-line framework for transforming warehouse and lakehouse data with SQL, modular models, version control, testing, documentation, lineage, and software-engineering workflows. dbt v2 is the Rust-based successor engine, while the prior release is referred to as dbt v1.
Hosted data-control-plane and Analytics Development Lifecycle platform for developing, testing, deploying, orchestrating, documenting, cataloging, and governing dbt projects.
Rust-based transformation engine with native SQL comprehension, much faster parsing, live error detection, IntelliSense, refactoring, state-aware orchestration, and cost-management capabilities.
Defines governed, consistent metrics and delivers them to dashboards, applications, and LLM/AI workflows.
Market Position
dbt Labs positions dbt as the standard transformation and analytics-engineering layer between raw data platforms and BI/AI consumers: an open, SQL- and Git-native alternative or complement to proprietary BI transformation, legacy ETL, and warehouse-specific tooling. It competes or overlaps with Google Dataform, Matillion, Informatica, Coalesce, Airflow-based transformation workflows, and native warehouse transformation features, while differentiating through its open-source community, cross-warehouse support, semantic/governance layer, and increasingly integrated AI and developer tooling.
Leadership
Founders
Tristan Handy
Data practitioner and former RJMetrics executive; he previously worked at analytics technology startups and founded Fishtown Analytics after leaving RJMetrics. He is dbt Labs' Founder and CEO.
Drew Banin
Joined Tristan Handy after working part-time as a software engineer at RJMetrics while completing college; co-founder and former Chief Product Officer of dbt Labs.
Connor McArthur
Software engineer and engineering leader who developed product, platform, and infrastructure at RJMetrics; also created the open-source VU-LEGO robotics target. He is a co-founder of dbt Labs.
Executive Team
Tristan Handy
Founder & CEO
More than two decades as a data practitioner across enterprises and startups; previously associated with RJMetrics and founded Fishtown Analytics.
Austin Stefani
Chief Revenue Officer
Former GVP of Americas Sales at Rubrik; previously held sales leadership roles at SAP and EMC.
Board of Directors
Founding Story
Tristan Handy started Fishtown Analytics in 2016 as a small Philadelphia consultancy to help startups improve their data systems. Handy and Drew Banin built dbt as an internal tool to make their consulting work faster, published it as open source, and discovered strong word-of-mouth demand. The consultancy gradually pivoted into a software company; it rebranded from Fishtown Analytics to dbt Labs in 2021.
Business Model
Revenue Model
Open-source dbt Core is free; dbt Labs monetizes hosted dbt Cloud and enterprise platform capabilities through custom subscriptions/contracts, with paid customer services and optional hosted dbt Charts Cloud. The company also sells AI capabilities whose model costs can be usage-dependent.
Pricing Tiers
dbt pricing page directs customers to contact sales; upfront commits and onboarding/professional services are available.
The Charts engine, CLI, and YAML language are free and open source.
Optional hosted product adding team features such as access control, Git-backed editing, and a shared warehouse connection.
Target Markets
- Enterprise data teams
- Analytics engineers and data engineers
- Data analysts and business intelligence teams
- Data platform and governance teams
- Companies using Snowflake, BigQuery, Databricks, Redshift, or other cloud warehouses/lakehouses
- Organizations building machine-learning and AI applications
- Analytics engineering and warehouse transformation
- Building reliable, tested, documented data models
- Enterprise data quality, governance, lineage, and discovery
- Self-service analytics and governed metrics
- Data platform modernization on cloud warehouses and lakehouses
- Preparing trusted structured data and context for AI applications and agents
- JetBlue
- HubSpot
- Dunelm
- Sunrun