Data Runs
on SDF

Data Run Better on SDF

SDF is a developer platform for data that scales SQL understanding across an organization, empowering all data teams to unlock the full potential of their data

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Your Developer First Data Platform

Debug 20x Faster with Static Analysis

Identify errors in your models without running them in the cloud. SDF’s static analysis identifies broken SQL and catches dependency errors before they hit production.

Leave VARCHARs behind with SDF Types

Elevate your models with user defined types. Prevent logic errors and validate your code with a type system that evolves with your warehouse.
Static data impact analysis with SDF Checks

An Analytical Database Built In

Context-aware execution that runs on your laptop and scales to the cloud. Powered by Apache DataFusion.
Static data impact analysis with SDF Checks

Secure your Development Workflows with Data Quality and Governance

Integrate data tests, governance reports, quality checks, and table statistics directly in your CI/CD. Use precise column-level lineage to track PII and represent business logic as code.

Working with Data has Never Been so Easy

Download the lightweight Rust binary and start running the SDF Engine locally in seconds. Experience the speed of a compiler with built-in caching and multi-threaded execution.
Debug SQL better than DBT with static analysis

SDF is Made for Developers

Try our product in under 30 seconds.

curl -LSfs | sh -s

Our Integrations

SDF powers the composable data stack by integrating with your unique configuration of cloud compute provider, storage format, and orchestrator.

Happy Developers Use SDF

SDF has been so much help with the schema migration. To just be able to compile and know that all of my downstream dependencies have been rewired is so huge. I have so much more confidence in my changes!

Nicklaus Roach
Data Engineer

SDF Labs is the new swiss army chainsaw for SQL. If you’re in the data space and want to get faster development cycles and greater safety, I strongly recommend checking them out.

Dylan Storey
Senior Director, Data Services
Domino Data Lab

It ensures that data models support company advancement while maintaining compliance and safeguarding sensitive information. By automating best practices and reinforcing data security, SDF stands as a cornerstone in scaling data infrastructures efficiently and responsibly.

Chris Hronek
Director of Data Engineering

“SDF has added order to chaos. Our development cycles have improved and we are able to focus on developing more models"

Vassili Skarine
Head of Engineering
Github Icon for SDF open source

Open Core with an Open Source Ecosystem

SDF is open core, powered by Apache Data Fusion. SDF Github libraries are open source, creating a community of collaborators.
See our Libraries

The Evolution of Data Development

DBT Core
Designed for SQL Development
Macro and Jinja Support
Column Level Lineage
Types & Classifications for SQL
SQL Static Analysis
Rich Materialization Options
Data Governance as Code
Rich Package Ecosystem
Integrated Caching Layer
Dependency Aware In Memory Database
Flexible Data Tests
Proactive Data Quality Checks
Generated Information Schema
Flexible Renaming and Environments


Can't find an answer to your question? Explore our docs or reach out to us directly.
Read our Docs
What is SDF?
SDF is a multi-dialect SQL compiler, transformation framework, and analytical database engine packaged into a single CLI. Unlike other data transformation tools like DBT, SDF extracts SQL compilers from their clouds, understanding proprietary dialects of SQL (like Snowflake) so deeply that it can ultimately execute them.

When working locally, SDF is both the Database, and Transformation layer, ensuring validity. Regardless of which Database you work with - at any point, the entirety of the Data Warehouse defined in your workspace is fully defined and statically analyzed as code. This makes SDF more like the build system for TypeScript or Rust than a traditional data development tool.
What is SDF used for?
The best data professionals unlock the full potential of their organization’s data through deep SQL understanding. SDF scales that SQL understanding across an organization.

Your data team can use SDF to:
- Prevent breaking changes from entering production through real-time impact analysis

- Develop faster with timely error reporting and isolated environments

- Gain precise column-level lineage for full warehouse transparency

- Integrate business logic into code through intelligent metadata and out-of-the-box guardrails

- Build your own data warehouses with an in-process analytical database
How do I get started with SDF?
Follow our 5-min introduction to SDF with our Getting Started guide

- Learn how SDF can help your data organization through our tutorials series

- Check out our how-to guides for advanced setup and features deep dives
How much does SDF cost?
The CLI is free to use. Support and the SDF Cloud are priced according to our Pricing Plans
Does SDF work with my Jinja?
Absolutely! SDF fully supports Jinja Macros, Templates, and SQL Variables. Dive deeper into these capabilities in our Macro Processing Overview document.

Want to stay up to date on SDF?

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Static impact analysis with SDF Checks
Catch SQL errors earlier than dbt with SDF
SDF SQL engine takes in SQL, Jinja, rules, and metadata to materialize tables, run data quality, and generate a data catalog.