November 4, 2025
Notebook wars: hold my popcorn
We're open-sourcing the successor of Jupyter notebook
Deepnote’s ‘Jupyter successor’ sparks backlash as rival tools trend
TLDR: Deepnote is open‑sourcing a claimed successor to Jupyter, promising AI‑ready, collaborative notebooks. Comments split: defenders say Jupyter needs no heir and critique the tone, while others point to alternatives like marimo or call it a Google Colab look‑alike—open source cheers meet heavy skepticism over the pitch.
Deepnote just dropped a bomb: they’re open‑sourcing what they call the “successor” to Jupyter, the popular notebook used by data folks everywhere. Their pitch? Jupyter is dated, teamwork is hard, and the future is reactive, collaborative, and AI‑ready. They even flash charts claiming fewer job postings asking for Jupyter and gripe about DIY setups costing teams time and money. Big claims, big energy—cue the comments section going full arena.
The crowd came in hot. One top reaction called the framing “nasty,” demanding respect for Jupyter. Another said flatly: “Jupyter does not have (or need) a successor.” Fans argued the post feels like marketing dressed as a eulogy. Confusion flared over the title, with readers thinking it was made by the Jupyter team; others said it just looks like Google Colab (a cloud notebook) with better UI and some AI chat sprinkled in. Meanwhile, the alt‑tool hype train rolled in: commenters plugged marimo, claiming it already replaced Jupyter for them—no drama needed. There was still some love for open source (“kudos for going oss”), but the vibe was: don’t crown a king while the old one’s still ruling. Meme energy: “import popcorn as p,” and “successor vs. Colab clone” jokes everywhere.
Key Points
- •Deepnote announced it is going open source and positions its platform as a successor to Jupyter notebooks.
- •The company argues teams need reactive, collaborative, AI‑ready notebooks and is opening its format and building blocks to support this.
- •It cites declining Jupyter-related job postings and slow activity in core Jupyter repos as indicators of shifting momentum.
- •The article details limitations of Jupyter notebooks at team scale: limited integrations, confusing UX, weak collaboration/versioning, brittle reproducibility, uneven visualization support, and no first‑class AI.
- •Deepnote criticizes the high total cost of ownership of JupyterHub-based internal platforms and promotes AI‑scaffolded, problem-first workflows designed to work across existing stacks.