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dbt Labs

Category: AI Developer Tools

dbt Labs provides a data transformation framework that enables data analysts and engineers to transform, test, and document data in the cloud data warehouse. dbt Labs was founded in 2016. The company is led by Tristan Handy. Based in Philadelphia, Pennsylvania, USA. Team size: 501-1000. Total funding raised: $414.4M. Latest round: Series D. Key investors include Altimeter, Databricks, Snowflake, GV, Salesforce Ventures.

Founded
2016
Headquarters
Philadelphia, Pennsylvania, USA
Team size
501-1000
Total funding
$414.4M

Value proposition

Brings software engineering best practices (version control, testing, documentation) to analytics workflows, enabling data teams to collaborate effectively and ship trusted data faster.

Products and solutions

dbt Core: An open-source command-line tool that enables data transformation using SQL., dbt Cloud: A managed cloud-based platform for developing, testing, scheduling, and deploying dbt projects., dbt Semantic Layer: Centrally defines key business metrics for consistent access across downstream analytics tools., dbt Fusion: An engine integrating dbt Core and the Semantic Layer for enhanced performance and capabilities., dbt Core v2.0 (alpha): Open-sourced Fusion engine runtime under Apache 2.0 license., dbt State: Caching layer for data pipelines that reduces infrastructure costs by 30%+., dbt Wizard (beta): Autonomous AI assistant for model authoring, refactoring, and debugging., Agents Schema: Open source standard for agentic context layer in warehouses.

Unique value

Pioneered Analytics Engineering by applying software engineering practices to data transformation. An open-source core (dbt Core) and a large active community have driven adoption and innovation.

Target customer

Data analysts, data engineers, and analytics engineers responsible for building and maintaining data pipelines and transforming raw data into analytics-ready datasets.

Industries served

Technology, Financial Services, Retail & E-commerce, Healthcare, Media & Entertainment, Consulting

Technology advantage

Empowers SQL-proficient data professionals to perform data engineering tasks, democratizing data transformation and enabling collaborative, efficient workflows. Strong integrations with Snowflake, Databricks, and BigQuery enhance platform fit.

How they differentiate

Focuses specifically on the transformation layer with software engineering best practices (version control, testing, documentation) and a strong open-source community around dbt Core, enabling analytics engineering.

Main competitors

Databricks, Snowflake, Matillion

Key partnerships

Snowflake, Databricks, Google Cloud, Amazon Web Services (AWS), Tableau, Microsoft Azure, Fivetran, OpenAI

Notable customers

JetBlue, HubSpot, Dunelm, SunRun, Nasdaq, Siemens, Condé Nast, Zendesk, DocuSign, Shutterstock

Major milestones

Pioneered the practice of 'analytics engineering', Reached a $4.2 billion valuation in February 2022, Surpassed $100 million in ARR, Grew the dbt community to over 100,000 data professionals, Merged with Fivetran in June 2026 to create data infrastructure for trusted AI agents

Growth metrics

80,000+ teams using dbt weekly; 5,700+ dbt Cloud customers; 100,000+ dbt Community members; 3,100+ Certified Analytics Engineers; combined revenue of $600M with Fivetran

Market positioning

Leader in the analytics engineering space and an industry standard for data transformation within the modern data stack.

Geographic focus

Global, strong presence in North America with expanding operations in Europe and Asia-Pacific.

Patents and IP

No publicly available information on patents; innovation is primarily embodied in open-source software and ecosystem.

About Tristan Handy

Tristan Handy is the Founder and CEO of dbt Labs. His career has been focused on data analytics and marketing. Prior to founding dbt Labs (originally Fishtown Analytics), he was the Vice President of Marketing at RJMetrics, co-founded Argyle Social, and held positions at Squarespace and RevBoss. His experience led to creation of dbt to solve data transformation challenges for analysts and engineers.

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