Notebooks weren't built for the modern data stack

Computational notebooks, despite being around for decades, have not kept up with the changes in the data world and feel outdated. The main issues with these tools are their inability to handle large amounts of data (scale), confusing and frustrating compute models (state), and lack of collaboration features (sharing). Despite these shortcomings, notebooks can be useful for iterative, exploratory data work but require users to overcome various challenges.