[eatonphil]

Thanks for asking! I hadn't seen it before but it looks pretty similar to Jupyter.

In both cases the audience for most traditional notebooks are data scientists. In contrast my target audience is backend developers and hands-on engineering managers who want to build operational and business dashboards and recurring email exports by combining data from multiple different data sources.

So it comes built in with setup for every major database. It can be run as a desktop app which makes it easier to get running than web-based notebooks, or as a web app where you can make dashboards and recurring email exports. And eventually my goal is to add high level connections to common APIs developers/managers use like Github, JIRA, Kubernetes controllers, etc. so you can build reports more easily across your services.

Also, the notebook interface on its own has felt to me like it doesn't treat querying databases as a first class thing. With DataStation the database query UI is separate from the programming UI. And like a SQL gui there's builtin support for specifying (encrypted) credentials to your various databases and builtin support for querying them over SSH proxies.

In contrast though Zeppelin and Jupyter are certainly much more mature and extensible.