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Conveyor is a platform for containerised data product deployment. It's goal is to make it as easy as possible to develop and support data products using code. For this reason we aid in the development, deployment, scalability and maintenance of data products.

Data products deployed on Conveyor can be created with any stack, platform or language with enhanced support for the following popular stacks: Spark and dbt.

Your data products are containerised using Docker, versioned in Git and can be deployed to a managed Conveyor cluster in your cloud account. Each cluster can contain multiple environments, each project can also be deployed to multiple environments. This enables you to deploy to development, test everything out and then promote that code to production.

For the convenience of developers, Conveyor includes comprehensive developer tools, and ready-to-go templates.

How is the documentation organised

Get started

This section contains introduction-level tutorials for data engineers and data analysts on how to use Conveyor.


The how-to guides describe step-by-step in depth topics like:

  • Key tasks and operations when working with Conveyor
  • Help to solve common problems

Technical reference

This topic covers tools, components, commands and resources.

Background information

Here we clarify and discuss key concepts of Conveyor.

Additional resources

Feature requests

If you would like new functionality to be added to Conveyor you can propose new functionality on our roadmap project.


If you want to follow along with our roadmap you can have a look here.


At Conveyor, we regularly release new versions (we typically aim for at lease one release per week). Each new version can contain bug fixes, improvements and new features. Keep track of our release notes.

Our promise to developers

Conveyor will help you achieve the same results as an experienced data engineer all by yourself. If you let us take care of the dull, repetitive jobs, you’ll get to do the creative, enjoyable ones.