Note: The quickstart section is for learning purposes. The installations described in this section will not persist your data.
For a production suitable deployment, deploy lakeFS on your cloud.
Spin up a lakeFS installation in seconds. Your installation will be available for 7 days.
- Install lakeFS on a Kubernetes cluster using Helm:
# Add the lakeFS Helm repository helm repo add lakefs https://charts.lakefs.io # Deploy lakeFS with helm release "my-lakefs" helm install my-lakefs lakefs/lakefs
The printed output will help you forward a port to lakeFS, so you can access it from your browser at http://127.0.0.1:8000/setup.
- Move on to create your first repository in lakeFS.
Alternatively, you may opt to run the lakefs binary directly on your computer.
Download the lakeFS binary for your operating system:
Create a configuration file:
--- database: type: local local: path: "~/lakefs/metadata" blockstore: type: "local" local: path: "~/lakefs/data"
Create a local directories to store objects and metadata:
mkdir -p ~/lakefs/data ~/lakefs/metadata
Run the server:
./lakefs --config /path/to/config.yaml run
Check your installation by opening http://127.0.0.1:8000/setup in your web browser.
You are now ready to create your first repository in lakeFS.
This Docker Compose application includes lakeFS together with other common data tools like Spark, dbt, Trino, Hive, and Jupyter.
Run the following commands to get the Bagel running:
- Clone the lakeFS repo:
git clone https://github.com/treeverse/lakeFS.git
- Start the Docker containers:
cd lakeFS/deployments/compose && docker compose up -d
Once the environment is running, open the UI for lakeFS by navigating to http://localhost:8000 in your browser.
The login credentials can be found in the
docker_compose.yml file in the
Once you are logged in, you should see a page that looks like below.
Note that a repository called
example is already created. If your lakeFS installation doesn’t have this repository, click the
Create Repository button to do so: