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The superduperdb open-source repository comes with a sandbox testing environment. The sandbox is implemented in docker-compose and includers containers for each of the services included in superduperdb. View the details of the setup here.

In this environment, users can test and get a feel for a full superduperdb setup, without the need to configure cloud environments or kubernetes setups. This environment may be used as inspiration for a more scalable, production-ready setup.

To build this environment first checkout the project if you haven't already:

git clone
cd superduperdb

Then build the docker image required to run the environment:

make testenv_image

If you want to install additional pip dependencies in the image, you have to list them in requirements.txt.

The listed dependencies may refer to:

  1. standalone packages (e.g tensorflow>=2.15.0)
  2. dependency groups listed in pyproject.toml (e.g .[demo,server])

Now add these configurations to your setup by running:

mkdir -p .superduperdb
cat << Multi > .superduperdb/config.yaml
data_backend: mongodb://superduper:superduper@mongodb:27017/test_db
cdc: http://cdc:8001
compute: dask://scheduler:8786
vector_search: in_memory://vector-search:8000

To start the environment run:

make testenv_init

This uses docker-compose to spin up:

  • local testing mongodb deployment
  • jupyter notebook environment
  • dask scheduler
  • dask worker
  • cdc service
  • vector-search service

To stop the environment run:

make testenv_shutdown

Known Issues

To make sure data is saved between restarts, we connect a local data location to the mongodb container. The location is specified in the SUPERDUPERDB_DATA_DIR of the Makefile and is initially set to deploy/testenv/.test_data.

However, since the mongodb container runs as 'root', the data directory will be owned by root, and you'll need sudo to delete it later.