awesome-data-science-notebook-engines
A collection of Data Science focused notebook engines
| Name |
URL |
Julia |
Notes |
| NextJounral |
https://nextjournal.com/ |
Yes |
- Good support for Julia
- cluttered and sometimes confusing interface
- allows you to build images; so pre-compiling is possible
|
| Jupyter |
|
Yes |
The original |
| Google Colab |
|
|
|
| CoCalc |
https://cocalc.com |
Yes |
- R, Python, Julia, and other languages
- Hundreds of GB of installed packages
- Jupyter notebooks, many kernels
- Rmd, LaTeX
- real-time collaboration
|
| MatrixDS |
|
Yes |
|
| MyBinder |
|
Yes; requires some tricks |
Binder |
| Kaggle |
|
No |
Proprietary |
| AWS SageMaker |
|
Not sure; suspect you can install the Julia kernel yourself |
Proprietary |
| Paper space |
https://www.paperspace.com/ |
Not sure |
Meant to be fast, not tested yet. |
| Observable |
https://Observablehq.com/ |
Not sure |
magic notebook for exploring data |
| Pluto |
https://github.com/fonsp/Pluto.jl |
Only Julia |
⚡ Lightweight reactive notebooks for Julia |
| Code Ocean |
https://codeocean.com/ |
|
|
| Elixir livebook |
https://github.com/elixir-nx/livebook |
no |
is it data science focused? probably not. |
| Name |
URL |
Notes |
| Juliabox |
|
Julia only; died on May 2020 |
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