Startups > dbt Labs

dbt Labs

dbt helps data teams transform raw warehouse data into analytics-ready insights.
Series D $416M total Founded 2016 Philadelphia, Pennsylvania
dbt Labs provides a data transformation platform that turns raw data in data warehouses into analysis-ready datasets through modular SQL queries, testing, and version control. The company offers dbt Core (open-source), dbt Cloud (hosted platform with IDE and job scheduling), and the dbt Semantic Layer for consistent metric management across BI tools. Used by over 40,000 companies including Nasdaq, JetBlue, and Canva, dbt has become the industry standard for analytics engineering in the modern data stack.
Problem solved
Data teams struggle to manage complex transformations of raw warehouse data, lacking version control, testing, and collaborative workflows for analytics engineering.
Target customer
Mid-market to enterprise companies with data warehouses (Snowflake, BigQuery, Redshift) and analytics teams needing reliable data transformation and governance.
Website LinkedIn Crunchbase
Founders
T
Tristan Handy
Co-Founder & CEO
Founded Fishtown Analytics (predecessor to dbt Labs) in 2016; angel investor in 12+ startups; led the company from data consulting to modern analytics platform.
D
Drew Banin
Co-Founder
Former Chief Product Officer; software engineer at 8tracks, RJMetrics, and Susquehanna International Group; computer science degree from Drexel University.
C
Connor McArthur
Co-Founder & CTO
Over a decade building enterprise data transformation tools; engineering leader at RJMetrics; computer engineering degree from Villanova University.
Funding history
Seed $1.5M November 2019 Led by Unknown · Unknown
Series A Unknown April 2020 Led by Andreessen Horowitz · Unknown
Series B Unknown November 2020 Led by Andreessen Horowitz, Sequoia · Unknown
Series C $150M June 2021 Led by Altimeter, Sequoia, Andreessen Horowitz · Unknown
Series D $222M February 2022 Led by Altimeter · Amplify Partners, Andreessen Horowitz, Sequoia, Coatue, Tiger Global, ICONIQ Growth, GV, GIC
Total raised: $416M
Industries
Analytics Big Data Information Technology Open Source Software
Pricing
Free dbt Core (open-source). dbt Cloud Starter at $100/seat/month (up to 5 developers, 15k models, 5k metrics). Enterprise tier with higher limits (100k models, 20k metrics, 30 projects) and custom pricing. Additional costs for compute consumption and advanced features (Semantic Layer, discovery, governance).
Notable customers
Nasdaq, JetBlue, Lendlease, Dunelm, Canva, McDonald's, Whatnot
Integrations
Snowflake, BigQuery, Redshift, Databricks, Postgres, dbt Semantic Layer integrations with Looker, Tableau, Power BI, Sisense
Website
getdbt.com/
Competitors
Fivetran
Fivetran focuses on data integration and ELT pipelines, while dbt specializes in the transformation layer after data is loaded.
Informatica
Informatica is an enterprise data integration platform covering extract, load, and transform; dbt focuses specifically on the transform phase with modern development practices.
Ascend
Ascend provides end-to-end data orchestration, while dbt is purpose-built for SQL-based transformation and analytics engineering workflows.
Dataiku
Dataiku offers broader data science and ML capabilities with GUI-based workflows, while dbt emphasizes code-first, SQL-native transformation.
Why this matters: dbt Labs has become the industry standard for analytics engineering, establishing a thriving open-source community while scaling to $4.2B valuation. The company is expanding beyond transformation into semantic layers and governance, positioning itself as a central hub in the modern data stack.
Best for: Analytics engineers and data teams at mid-market to enterprise companies who need reliable, version-controlled data transformations with testing and collaboration.
Use cases
Data Warehouse Transformation at Scale
Large enterprises with complex data warehouses use dbt to organize hundreds of transformation models, maintain data lineage, and ensure data quality across thousands of daily jobs. Teams version control transformations like code, run automated tests, and document data dependencies across the organization.
Analytics Engineering for Startups
Series A-C startups use dbt Core (free) to build repeatable analytics infrastructure without hiring expensive data engineers. Teams write modular SQL transformations, version control changes, and collaborate on metric definitions as the company scales.
Centralized Metric Management
Organizations use dbt Semantic Layer to define metrics once and expose them consistently across Looker, Tableau, and other BI tools, eliminating metric definition conflicts and speeding up self-service analytics.
Alternatives
Fivetran Choose Fivetran if you need end-to-end ELT (extract and load) in addition to transformation; dbt is transformation-only.
Dataiku Choose Dataiku if you need visual, low-code workflows and advanced ML capabilities alongside data transformation.
Apache Airflow Choose Airflow if you need a general-purpose orchestration framework; dbt is specialized for SQL transformation workflows with built-in testing and lineage.
FAQ
What does dbt Labs do? +
dbt Labs provides tools for data transformation in modern cloud data warehouses. The company offers dbt Core (free, open-source), dbt Cloud (hosted platform with IDE and job scheduling), and dbt Semantic Layer (centralized metric definitions). dbt enables analytics engineers to write modular SQL transformations, test data quality, version control projects, and collaborate on analytics workflows.
How much does dbt cost? +
dbt Core is free and open-source. dbt Cloud Starter costs $100/seat/month for up to 5 developers with 15k models and 5k metrics. Enterprise plans offer higher limits and custom pricing. Additional costs apply for compute consumption and advanced features like the Semantic Layer.
Who uses dbt? +
Over 40,000 companies use dbt in production, including Nasdaq, JetBlue, Canva, Lendlease, and McDonald's. The user base ranges from startups using free dbt Core to large enterprises running dbt Cloud with enterprise governance and semantic layers.
How does dbt compare to Fivetran? +
Fivetran handles data extraction and loading (ELT), while dbt specializes in the transformation layer that comes after data is in the warehouse. Many companies use both together: Fivetran to move data, dbt to transform it. dbt is SQL-native and code-first, while Fivetran is UI-driven for connectors.
What is dbt Semantic Layer? +
dbt Semantic Layer enables organizations to define business metrics once and expose them consistently across Looker, Tableau, Power BI, and other BI tools. This eliminates metric definition conflicts and accelerates self-service analytics by ensuring all stakeholders use the same metric definitions.
Tags
data transformation analytics engineering SQL open source data warehousing semantic layer modern data stack