Apache Superset now with IRIS

Apache Superset is a modern data exploration and data visualization platform. Superset can replace or augment proprietary business intelligence tools for many teams. Superset integrates well with a variety of data sources.

And now it is possible to use with InterSystems IRIS as well.

An online demo is available and it uses IRIS Cloud SQL as a data source.

Apache Superset provides a bunch of examples, which were successfully loaded to IRIS without any issues, and displayed on example dashboards.

The support for IRIS is implemented with a Python package named superset-iris, which can be installed in Superset installed manually.

Superset uses SQLAlchemy as an engine for a database, so, the package superset-iris uses sqlalchemy-iris.

When the package is installed in the Superset environment, it becomes possible to select InterSystems IRIS from the list of supported databases.

To connect to IRIS database, it requires SQLAlchemy URI in form iris://{login}:{password}@{hostname}:{port}/{namespace}

Test connection should check if the server is available. And Then press Connect, to finish adding the database.

In the same editing database form, on the Advanced Tab, and in Security block, option named Allow file uploads to database, which will allow to upload CSV files and construct tables with data in IRIS based on it.

SQL Lab, allows doing SQL Queries

As well as collect and display information about existing Schemas and tables in it, preview those tables and offers to construct a simple SQL Query with all columns.

To try it locally. Clone the repository

git clone https://github.com/caretdev/superset-iris.git superset-iris
cd superset-iris

Start Superset with Docker-Compose

docker-compose pull
docker-compose up -d

During the start it imports example data to IRIS Database, it will take a while, to wait until it's done, run this command

docker-compose logs -f superset-init

When the command above finishes working, go to http://localhost:8088/dashboard/list/. Dashboards are available without authorization. To access SQL Lab use admin/admin as login and password.

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