[sireat]

what would be advantages to going to Deepnote from regular Jupyter notebooks based workflow?

Let's assume someone who has been working with Jupyter notebooks(mostly Python based) for a long time.

Are Deepnote notebooks exportable?

The big worry is that you guys decide to pivot or radically change your pricing model and there is no offramp.

By comparison I don't mind using Google Colab. If Google Colab decides to shutdown or 100x their price I can take my .ipynb files and use them on my local littlest JupyterHub instance.

[d_rc]

Deepnote internally supports .ipynb format and you can always export the Deepnote notebook to .ipynb similarly as you'd in Colab.

In general the main selling points are live collaboration (you can work on a notebook with you team as you'd do on a google doc), and integrations (you can plug-in your snowflake db, or s3 bucket or whatever, and have it connected for any further analysis, or a long-term training, etc.

For many non-software-developer data scientists, it's also easier to work in a cloud environment compared to installing stuff locally, and to version their notebooks in Deepnote instead of git. But this really depends on the particular workflow that one has.

[sireat]

Thank you for the answers!

I can absolutely see a need for collaboration tool. Collaboration on regular Jupyter is a pain. I create a shared folder for coworkers and well read/write permissions* are not fun.

* knows chmod - https://www.reddit.com/r/linux/comments/dily0/i_know_how_to_...