- Well, notebook programming environments can be really handy for doing certain types of interactive or exploratory development.
- There is quite a few of them.
SQL & Python
- Deepnote
- Free for individuals/small teams
- SQL + Python
- Modern-looking
- Buzz, Czech
- All in UI, including versioning
- Should be integrated with dbt
- Hex
- Free for individuals
- Python + SQL + vizzes
- Modern-looking, most of the features
- Generates buzz
- Only UI version-control and collaboration
- More info on how it works here
- How could it work with dbt?
- dbt Cloud integration
Python
- Jupyter Notebook
- Streamlit
- Interactive data apps built in Python, directly from Github
- Enables data caching
- Mostly built for ML though
- Gradio
- Build & share delightful ML apps
- Quick to set up, using Python
- Similar to Streamlit
- Marimo
- The future of Python notebooks
- No baggage, very nicely works even in virtual env, no extensions
- Solves a lot of issues of standard Jupyter notebooks
- Itself written and run in Python and nothing else – easier to git-version etc.
- Has Copilot and Black out of the box
SQL
- Evidence
- Markdown + SQL + vizes
- Open-source
- dbt integration
- Code-based, so version control in repo is an option
- Tellery
- SQL + simple vizes
- Open-source
- dbt integration
- All in UI
- Husprey
- Not sure about pricing
- SQL + vizes
- Modern, but not so shiny as the others
- Not too much info
- Count
- Free for individuals
- Only SQL + vizzes
- Works like CTEs
- Modern-looking, drag-and-drop
- Version control in UI, but with forking and merging