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Using Docker Compose


Since docker-compose is primarily designed to run a set of containers on a single host and can't support requirements for high availability, we do not support nor recommend using our docker-compose constructs to support production-type use-cases. For single host environments, we recommend using minikube along our installing on k8s documentation.

As mentioned in our quickstart guide, the fastest way to try Superset locally is using Docker Compose on a Linux or Mac OSX computer. Superset does not have official support for Windows. It's also the easiest way to launch a fully functioning development environment quickly.

Note that there are 3 major ways we support to run docker-compose:

  1. docker-compose.yml: for interactive development, where we mount your local folder with the frontend/backend files that you can edit and experience the changes you make in the app in real time
  2. docker-compose-non-dev.yml where we just build a more immutable image based on the local branch and get all the required images running. Changes in the local branch at the time you fire this up will be reflected, but changes to the code while up won't be reflected in the app
  3. docker-compose-image-tag.yml where we fetch an image from docker-hub say for the 3.0.0 release for instance, and fire it up so you can try it. Here what's in the local branch has no effects on what's running, we just fetch and run pre-built images from docker-hub

More on these two approaches after setting up the requirements for either.


Note that this documentation assumes that you have Docker, docker-compose, and git installed.

1. Clone Superset's GitHub repository

Clone Superset's repo in your terminal with the following command:

git clone --depth=1

Once that command completes successfully, you should see a new superset folder in your current directory.

2. Launch Superset Through Docker Compose

First let's assume you're familiar with docker-compose mechanics. Here we'll refer generally to docker compose up even though in some cases you may want to force a check for newer remote images using docker compose pull, force a build with docker compose build or force a build on latest base images using docker compose build --pull. In most cases though, the simple up command should do just fine. Refer to docker compose docs for more information on the topic.

Option #1 - for an interactive development environment

docker compose up

When running in development mode the superset-node container needs to finish building assets in order for the UI to render properly. If you would just like to try out Superset without making any code changes follow the steps documented for production or a specific version below.


By default, we mount the local superset-frontend folder here and run npm install as well as npm run dev which triggers webpack to compile/bundle the frontend code. Depending on your local setup, especially if you have less than 16GB of memory, it may be very slow to perform those operations. In this case, we recommend you set the env var BUILD_SUPERSET_FRONTEND_IN_DOCKER to false, and to run this locally instead in a terminal. Simply trigger npm i && npm run dev, this should be MUCH faster.

Option #2 - build a set of immutable images from the local branch

docker compose -f docker-compose-non-dev.yml up

Option #3 - boot up an official release

export TAG=3.1.1
docker compose -f docker-compose-image-tag.yml up

Here various release tags, github SHA, and latest master can be referenced by the TAG env var. Refer to the docker-related documentation to learn more about existing tags you can point to from Docker Hub.

docker-compose tips & configuration


All of the content belonging to a Superset instance - charts, dashboards, users, etc. - is stored in its metadata database. In production, this database should be backed up. The default installation with docker compose will store that data in a PostgreSQL database contained in a Docker volume, which is not backed up.


You should see a stream of logging output from the containers being launched on your machine. Once this output slows, you should have a running instance of Superset on your local machine! To avoid the wall of text on future runs, add the -d option to the end of the docker compose up command.

Configuring Further

The following is for users who want to configure how Superset runs in Docker Compose; otherwise, you can skip to the next section.

You can install additional python packages and apply config overrides by following the steps mentioned in docker/

Note that docker/.env sets the default environment variables for all the docker images used by docker-compose, and that docker/.env-local can be used to override those defaults. Also note that docker/.env-local is referenced in our .gitignore, preventing developers from risking committing potentially sensitive configuration to the repository.

One important variable is SUPERSET_LOAD_EXAMPLES which determines whether the superset_init container will populate example data and visualizations into the metadata database. These examples are helpful for learning and testing out Superset but unnecessary for experienced users and production deployments. The loading process can sometimes take a few minutes and a good amount of CPU, so you may want to disable it on a resource-constrained device.

For more advanced or dynamic configurations that are typically managed in a file located in your PYTHONPATH, note that it can be done by providing a docker/pythonpath_dev/ that will be ignored by git (preventing you to commit/push your local configuration back to the repository). The mechanics of this are in docker/pythonpath_dev/ where you can see that the logic runs a from superset_config_docker import *


Users often want to connect to other databases from Superset. Currently, the easiest way to do this is to modify the docker-compose-non-dev.yml file and add your database as a service that the other services depend on (via x-superset-depends-on). Others have attempted to set network_mode: host on the Superset services, but these generally break the installation, because the configuration requires use of the Docker Compose DNS resolver for the service names. If you have a good solution for this, let us know!


Superset uses Scarf Gateway to collect telemetry data. Knowing the installation counts for different Superset versions informs the project's decisions about patching and long-term support. Scarf purges personally identifiable information (PII) and provides only aggregated statistics.

To opt-out of this data collection for packages downloaded through the Scarf Gateway by your docker compose based installation, edit the x-superset-image: line in your docker-compose.yml and docker-compose-non-dev.yml files, replacing with apache/superset to pull the image directly from Docker Hub.

To disable the Scarf telemetry pixel, set the SCARF_ANALYTICS environment variable to False in your terminal and/or in your docker/.env file.

3. Log in to Superset

Your local Superset instance also includes a Postgres server to store your data and is already pre-loaded with some example datasets that ship with Superset. You can access Superset now via your web browser by visiting http://localhost:8088. Note that many browsers now default to https - if yours is one of them, please make sure it uses http.

Log in with the default username and password:

username: admin
password: admin

4. Connecting Superset to your local database instance

When running Superset using docker or docker compose it runs in its own docker container, as if the Superset was running in a separate machine entirely. Therefore attempts to connect to your local database with the hostname localhost won't work as localhost refers to the docker container Superset is running in, and not your actual host machine. Fortunately, docker provides an easy way to access network resources in the host machine from inside a container, and we will leverage this capability to connect to our local database instance.

Here the instructions are for connecting to postgresql (which is running on your host machine) from Superset (which is running in its docker container). Other databases may have slightly different configurations but gist would be same and boils down to 2 steps -

  1. (Mac users may skip this step) Configuring the local postgresql/database instance to accept public incoming connections. By default, postgresql only allows incoming connections from localhost and under Docker, unless you use --network=host, localhost will refer to different endpoints on the host machine and in a docker container respectively. Allowing postgresql to accept connections from the Docker involves making one-line changes to the files postgresql.conf and pg_hba.conf; you can find helpful links tailored to your OS / PG version on the web easily for this task. For Docker it suffices to only whitelist IPs instead of *, but in any case you are warned that doing this in a production database may have disastrous consequences as you are opening your database to the public internet.
  2. Instead of localhost, try using host.docker.internal (Mac users, Ubuntu) or (Linux users) as the hostname when attempting to connect to the database. This is a Docker internal detail -- what is happening is that, in Mac systems, Docker Desktop creates a dns entry for the hostname host.docker.internal which resolves to the correct address for the host machine, whereas in Linux this is not the case (at least by default). If neither of these 2 hostnames work then you may want to find the exact hostname you want to use, for that you can do ifconfig or ip addr show and look at the IP address of docker0 interface that must have been created by Docker for you. Alternately if you don't even see the docker0 interface try (if needed with sudo) docker network inspect bridge and see if there is an entry for "Gateway" and note the IP address.