dbt Labs provides tools that enable data teams to build and deploy analytics code using software engineering best practices. The platform facilitates the transformation of raw data into trusted, production-ready assets within the data warehouse. This focus on the analytics development lifecycle helps organizations scale their data transformation workflows efficiently.
Funding
$9M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Data teams often struggle with identifying SQL errors before production, leading to broken data pipelines and inaccurate insights. Traditional data transformation tools lack robust type systems and integrated data quality checks, hindering development speed and data governance.
Solution
SDF is a developer platform that combines a multi-dialect SQL compiler, transformation framework, and analytical database engine to enhance data engineering workflows. It enables data teams to identify SQL errors through static analysis, implement user-defined types for data validation, and integrate data quality checks directly into CI/CD processes. SDF's context-aware execution runs locally and scales to the cloud, powered by Apache DataFusion. The platform provides column-level lineage to track PII and represent business logic as code, ensuring data models support company advancement while maintaining compliance and safeguarding sensitive information.
Target Audience
SDF targets data engineers, data scientists, and data analysts who need to build and maintain reliable data pipelines and ensure data quality across their organizations.
Features
- Multi-dialect SQL compiler that understands proprietary SQL dialects
- Static analysis to identify broken SQL and dependency errors before production
- User-defined types to prevent logic errors and validate code
- Integrated data quality and governance reports directly in CI/CD
- Column-level lineage to track PII
- In-process analytical database for local development and testing
- Support for Jinja macros, templates, and SQL variables
- Lightweight Rust binary for fast local execution with built-in caching and multi-threaded execution