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Org mode VS Jupyter

Compare Org mode VS Jupyter and see what are their differences

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Org mode logo Org mode

Org: an Emacs Mode for Notes, Planning, and Authoring

Jupyter logo Jupyter

Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
  • Org mode Landing page
    Landing page //
    2022-04-15
  • Jupyter Landing page
    Landing page //
    2023-06-22

Org mode features and specs

  • Seamless Integration with Emacs
    Org mode is tightly integrated with Emacs, allowing users to take full advantage of Emacs' powerful text-editing capabilities and extensive customization options.
  • Outline-Based Workflow
    Org mode supports hierarchical organization of information, which makes it easy to structure content in a clear, logical manner and manage complex documents or projects.
  • Task Management
    Built-in TODO lists, scheduling, and deadline management features make it a powerful tool for personal productivity and project management.
  • Export Capabilities
    Org mode can export documents to a variety of formats including HTML, LaTeX, PDF, and Markdown, making it versatile for different publishing needs.
  • Customizability
    Highly customizable through Emacs Lisp, allowing users to tailor Org mode to their specific workflow requirements.
  • Community and Extensions
    A robust community and numerous extensions are available, providing additional functionality and support.

Possible disadvantages of Org mode

  • Steep Learning Curve
    Requires significant time and effort to learn, especially for users who are not already familiar with Emacs.
  • Emacs Dependency
    Org mode is dependent on Emacs, which might not appeal to users who prefer different text editors or Integrated Development Environments (IDEs).
  • Complexity
    While it's powerful, the extensive features and customization options can become overwhelming and lead to a complex setup.
  • Lack of Standalone Version
    There is no standalone version of Org mode; it requires Emacs, which can be a barrier for those who do not want to use Emacs.
  • User Interface
    The text-based interface might not be as intuitive or visually appealing as modern, graphical task management or note-taking applications.

Jupyter features and specs

  • Interactive Computing
    Jupyter allows real-time interaction with the data and code, providing immediate feedback and making it easier to experiment and iterate.
  • Rich Media Output
    It supports output in various formats including HTML, images, videos, LaTeX, and more, enhancing the ability to visualize and interpret results.
  • Language Agnostic
    Jupyter supports multiple programming languages through its kernel system (e.g., Python, R, Julia), allowing flexibility in the choice of tools.
  • Collaborative Features
    It enables collaboration through shared notebooks, version control, and platform integrations like GitHub.
  • Educational Tool
    Jupyter is widely used for teaching, thanks to its easy-to-use interface and ability to combine narrative text with code, making it ideal for assignments and tutorials.
  • Extensibility
    Jupyter is highly extensible with a large ecosystem of plugins and extensions available for various functionalities.

Possible disadvantages of Jupyter

  • Performance Issues
    For larger datasets and more complex computations, Jupyter can be slower compared to running scripts directly in a dedicated IDE.
  • Version Control Challenges
    Managing version control for Jupyter notebooks can be cumbersome, as they are not plain text files and include metadata that can make diffing and merging complex.
  • Resource Intensive
    Running Jupyter notebooks can be resource-intensive, especially when working with multiple large notebooks simultaneously.
  • Security Concerns
    Because Jupyter allows code execution in the browser, it can be a potential security risk if notebooks from untrusted sources are run without restrictions.
  • Dependency Management
    Managing dependencies and ensuring that the notebook runs consistently across different environments can be challenging.
  • Less Suitable for Production
    Jupyter is often considered more as a research and educational tool rather than a production environment; transitioning from a notebook to production code can require significant refactoring.

Org mode videos

+ Add

org mode is awesome

More videos:

  • Review - 2018-11-14: Building a Second Brain in Org Mode - Tasshin Michael Fogleman

Jupyter videos

+ Add

What is Jupyter Notebook?

More videos:

  • Tutorial - Jupyter Notebook Tutorial: Introduction, Setup, and Walkthrough
  • Review - JupyterLab: The Next Generation Jupyter Web Interface

Category Popularity

0-100% (relative to Org mode and Jupyter)

Org mode

Jupyter

Task Management
100 100%
Task Management
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Project Management
100 100%
Project Management
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100

User comments

Share your experience with using Org mode and Jupyter. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Org mode and Jupyter

Org mode Reviews

Ask HN: Favorite note-taking software?
Before going full Org Mode, I used MS OneNote, and liked it very much. My notes from that period has tons of images and annotated screenshots dumped into them. I miss that in my Emacs workflow nowadays. My dream software would be pieces of Org Mode on a OneNote-like canvas, with support for easily pasting images and drawing on them (especially using a graphics tablet, or at...
Source: news.ycombinator.com

Jupyter Reviews

Jupyter Notebook & 10 Alternatives: Data Notebook Review [2023]
Once you install nteract, you can open your notebook without having to launch the Jupyter Notebook or visit the Jupyter Lab. The nteract environment is similar to Jupyter Notebook but with more control and the possibility of extension via libraries like Papermill (notebook parameterization), Scrapbook (saving your notebook’s data and photos), and Bookstore (versioning).
Source: lakefs.io
7 best Colab alternatives in 2023
JupyterLab is the next-generation user interface for Project Jupyter. Like Colab, it's an interactive development environment for working with notebooks, code, and data. However, JupyterLab offers more flexibility as it can be self-hosted, enabling users to use their own hardware resources. It also supports extensions for integrating other services, making it a highly...
Source: deepnote.com
12 Best Jupyter Notebook Alternatives [2023] – Features, pros & cons, pricing
Jupyter Notebook is a widely popular tool for data scientists to work on data science projects. This article reviews the top 12 alternatives to Jupyter Notebook that offer additional features and capabilities.
Source: noteable.io
15 data science tools to consider using in 2021
Jupyter Notebook's roots are in the programming language Python -- it originally was part of the IPython interactive toolkit open source project before being split off in 2014. The loose combination of Julia, Python and R gave Jupyter its name; along with supporting those three languages, Jupyter has modular kernels for dozens of others.
Source: searchbusinessanalytics.techtarget.com
Top 4 Python and Data Science IDEs for 2021 and Beyond
Yep — it’s the most popular IDE among data scientists. Jupyter Notebooks made interactivity a thing, and Jupyter Lab took the user experience to the next level. It’s a minimalistic IDE that does the essentials out of the box and provides options and hacks for more advanced use.
Source: towardsdatascience.com

Social recommendations and mentions

Jupyter might be a bit more popular than Org mode. We know about 216 links to it since March 2021 and only 180 links to Org mode. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Org mode mentions (180)

  • Ask HN: Static Site (not blog) Generator?
    My favorite static site generator is Org mode[1] for Emacs. Org files are written using a feature-rich lightweight markup language[2] that is much more powerful than Markdown (e.g., plain text spreadsheets). Org files can be exported to HTML[3]. The reason I prefer Org for static site generation is not because I already use Emacs. I actually started using Emacs about 20 years ago specifically to use Org mode. [1]... - Source: Hacker News / 1 day ago
  • Reinventing notebooks as reusable Python programs
    "until recently, Jupyter notebooks were the only programming environment that let you see your data while you worked on it." This is false. Org-mode has had this functionality for over two decades. https://orgmode.org/. - Source: Hacker News / about 2 months ago
  • Emacs 2024 Changes
    Work - I use org-mode heavily for my personal project management and note keeping. - Source: dev.to / 4 months ago
  • My 2024 review
    While embracing analog tools, I've also refined my digital organization using ORG mode in Emacs. The system has evolved to become more structured and efficient. - Source: dev.to / 5 months ago
  • (Game)Dev with Emacs - Because it's not Already Hard Enough Without it
    Org mode. Org mode is just great for taking notes and organizing tasks. I might write a post on it one day. If you're interested, check out Org Mode in the mean time. - Source: dev.to / 8 months ago
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Jupyter mentions (216)

  • The 3 Best Python Frameworks To Build UIs for AI Apps
    Showcase and share: Easily embed UIs in Jupyter Notebook, Google Colab or share them on Hugging Face using a public link. - Source: dev.to / about 2 months ago
  • LangChain: From Chains to Threads
    LangChain wasn’t designed in isolation — it was built in the data pipeline world, where every data engineer’s tool of choice was Jupyter Notebooks. Jupyter was an innovative tool, making pipeline programming easy to experiment with, iterate on, and debug. It was a perfect fit for machine learning workflows, where you preprocess data, train models, analyze outputs, and fine-tune parameters — all in a structured,... - Source: dev.to / 3 months ago
  • Applied Artificial Intelligence & its role in an AGI World
    Leverage versatile resources to prototype and refine your ideas, such as Jupyter Notebooks for rapid iterations, Google Colabs for cloud-based experimentation, OpenAI’s API Playground for testing and fine-tuning prompts, and Anthropic's Prompt Engineering Library for inspiration and guidance on advanced prompting techniques. For frontend experimentation, tools like v0 are invaluable, providing a seamless way to... - Source: dev.to / 4 months ago
  • Jupyter Notebook for Java
    Lately I've been working on Langgraph4J which is a Java implementation of the more famous Langgraph.js which is a Javascript library used to create agent and multi-agent workflows by Langchain. Interesting note is that [Langchain.js] uses Javascript Jupyter notebooks powered by a DENO Jupiter Kernel to implement and document How-Tos. So, I faced a dilemma on how to use (or possibly simulate) the same approach in... - Source: dev.to / 8 months ago
  • JIRA Analytics with Pandas
    One of the most convenient ways to play with datasets is to utilize Jupyter. If you are not familiar with this tool, do not worry. I will show how to use it to solve our problem. For local experiments, I like to use DataSpell by JetBrains, but there are services available online and for free. One of the most well-known services among data scientists is Kaggle. However, their notebooks don't allow you to make... - Source: dev.to / 11 months ago
View more

What are some alternatives?

When comparing Org mode and Jupyter, you can also consider the following products

Todoist - Todoist is a to-do list that helps you get organized, at work and in life.

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

Workflowy - A better way to organize your mind.

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

Trello - Infinitely flexible. Incredibly easy to use. Great mobile apps. It's free. Trello keeps track of everything, from the big picture to the minute details.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

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