Slow & local data allows you to move fast and deliver business value for the 99.9% of the data challenges.
Last updated Jul 7, 2026
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README
local data stack template
This template brings together some of the best open-source tools in data engineering and Rust-based tooling for ensuring code quality:
- dagster, dbt, duckdb
- pixi
- docker
- ruff, pyright, taplo, pytest
- cruft
The idea of slow data refers to:
- focusing on the reduction of complexity
- shipping real busines value fast
- scaling as needed via partitions and a scalable resource provider
The template directly can be deployed via docker-compose. With only minimal adaptations you can instead deploy to kubernetes in any cloud provider.
Additionally included for secure handling of secrets:
- sops
- age
usage
Prerequisites:
- git
- an installation of cruft
pip install cruft jinja2-ospath - an installation of pixi https://pixi.sh/latest/#installation
curl -fsSL https://pixi.sh/install.sh | bash - text editor of choice such as vscode
- docker
curl -fsSL https://pixi.sh/install.sh | bash
git clone https://github.com/l-mds/local-data-stack.git
cd local-data-stack
pixi run tpl-init-cruft
alternatively:
pip install cruft jinja2-ospath
cruft create https://github.com/l-mds/local-data-stack.git
cd <<your project name>> git init git add . git commit -m "initial commit"
pixi update git commit -m "set dependencies"
git commit -m "reformatting" pixi run fmt
set dagster home to some directory
your logs and run results will be persistet there
mkdir /path/to/mydagsterhome
export DAGSTERHOME=/path/to/mydagster_home
start the data stack
pixi run start-dev
Post install:
- update the secrets in the
.envfiles by executing:openssl rand -base64 32and setting a suitable secret - ensure the
.env.enccan be created by following the instructions in [documentation/secops]
Developing the template
To render an instance of the project:
pixi run render-dev🔗 More in this category