Gerhard Brueckl tells us what comes after notebooks for users with development backgrounds:
For those users Databricks has developed Databricks Connect (Azure docs) which allows you to work with your local IDE of choice (Jupyter, PyCharm, RStudio, IntelliJ, Eclipse or Visual Studio Code) but execute the code on a Databricks cluster. This is awesome and provides a lot of advantages compared to the standard notebook UI. The two most important ones are probably the proper integration into source control / git and the ability to extend your IDE with tools like automatic formatters, linters, custom syntax highlighting, …
While Databricks Connect solves the problem of local execution and debugging, there was still a gap when it came to pushing your local changes back to Databricks to be executed as part of a regular ETL or ML pipeline. So far you had to either “deploy” your changes by manually uploading them via the Databricks UI again or write a script that uploads it via the REST API (Azure docs).
Gerhard has a nice extension for Visual Studio Code which helps with this. I’m also a huge fan of the DatabricksPS module, so I’ll happily plug that here.