![]() ![]() 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, … ![]() This is awesome and provides a lot of advantages compared to the standard notebook UI. ![]() Especially nowadays, where a lot of data engineers and scientists have a strong background also in regular software development and expect the same features that they are used to from their original Integrated Development Environments (IDE) also in Databricks.įor those users Databricks has developed Databricks Connect ( Azure docs) which allows you to work with your local IDE of choice (Jupyter, P圜harm, RStudio, IntelliJ, Eclipse or Visual Studio Code) but execute the code on a Databricks cluster. This is perfectly fine for most of the use cases but sometimes it is just not enough. When working with Databricks you will usually start developing your code in the notebook-style UI that comes natively with Databricks. ![]()
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