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Jupyter VS Logseq

Compare Jupyter VS Logseq and see what are their differences

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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.

Logseq logo Logseq

Logseq is a local-first, non-linear, outliner notebook for organizing and sharing your personal knowledge base.
  • Jupyter Landing page
    Landing page //
    2023-06-22
  • Logseq Landing page
    Landing page //
    2024-10-15

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.

Logseq features and specs

  • Bidirectional Linking
    Logseq allows users to easily create bidirectional links between notes, enhancing organization and navigation through related information.
  • Graph View
    The graph view provides a visual representation of how notes are interconnected, helping users see the bigger picture of their knowledge network.
  • Markdown Support
    Logseq supports Markdown, making it easy to format notes and write in a widely-used plain text format.
  • Local Storage
    Notes are stored locally, giving users full control over their data and enhancing privacy and security.
  • Customizable Workflows
    Users can customize their workflows with plugins and templates to suit their specific needs and preferences.
  • Open Source
    Being an open-source project, Logseq invites community contributions and ensures more transparency in development and issue resolution.
  • Task Management
    Logseq integrates task management features, such as to-do lists and scheduling, directly within notes, improving productivity.

Possible disadvantages of Logseq

  • Learning Curve
    New users may find Logseq's extensive features and unique workflow approach challenging to learn without dedicated time and effort.
  • Sync Complexity
    While storing notes locally is a pro for privacy, it requires additional tools or manual methods to sync notes across multiple devices.
  • Mobile App Limitations
    The mobile version of Logseq is still in development, meaning it may lack some features and fluidity found in the desktop version.
  • Resource Intensive
    Logseq can consume considerable system resources, particularly when dealing with large datasets or extensive use of graph view.
  • Community Dependency
    As an open-source project, certain features may rely on community contributions, which could lead to inconsistent updates or support.
  • Customization Complexity
    While high customization is a benefit, it can become overwhelming and complex to manage for users who prefer a more straightforward tool.

Analysis of Logseq

Overall verdict

  • Yes, Logseq is generally considered a good tool, particularly for individuals seeking a robust, free-form method of organizing notes and knowledge that goes beyond traditional hierarchical models.

Why this product is good

  • Logseq is a versatile tool for managing notes and knowledge using a graph-based interface similar to networked thought processing. It offers features like linked references, back-linking, and support for Markdown and org-mode, making it a valuable tool for those who value interconnected note-taking. Its open-source nature ensures constant community-driven improvements and transparency, encouraging a strong user community.

Recommended for

  • Students and researchers who manage a large volume of interconnected notes.
  • Professionals who require a flexible and dynamic knowledge management system.
  • Writers and content creators looking for a tool to visualize ideas and concepts.
  • Tech enthusiasts and developers who appreciate open-source software.

Jupyter videos

What is Jupyter Notebook?

More videos:

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

Logseq videos

Logseq - A Roam Research Alternative for Notes / PKM / To Do / Journal

More videos:

  • Review - How I use Logseq Daily - A Roam Research Alternative for Notes / PKM / To Do / Journal
  • Review - Logseq Update Video - A Roam Research Alternative for Notes / PKM / To Do / Journal

Category Popularity

0-100% (relative to Jupyter and Logseq)
Data Science And Machine Learning
Note Taking
0 0%
100% 100
Data Dashboard
100 100%
0% 0
Knowledge Management
0 0%
100% 100

User comments

Share your experience with using Jupyter and Logseq. 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 Jupyter and Logseq

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.
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.

Logseq Reviews

The 5 Best Open Source Miro Alternatives in 2024
Logseq is a powerful and advanced tool for thought that has been gaining attention among note-taking enthusiasts and productivity seekers. In this article, we will provide an overview of Logseq, explore what users can do with the tool, and highlight its strengths and weaknesses compared to Miro, another popular tool in the note-taking and organization space.
Source: affine.pro
Supercharge Your Productivity: Three Recommended Tools for Thought
Outliners (think Workflowy, Roam, Logseq) rely on blocks and indentation for primary connections, and references to other blocks or pages for richer links. They’re optimized for capturing quick thinking.
Source: medium.com
Logseq vs Roam Research vs Obsidian: which one should you choose?
Refined user interface: Logseq offers a refined user interface that is easy to understand and pleasing to the eyes. On the other hand, Obsidian looks like a jumble of various UI elements which are hard to figure out and look daunting. Logseq wins this round for me, hands down. – The only reason to choose Obsidian’s user interface over Logseq’s is that the former is far more...
Source: medium.com
Best 5 Obsidian Alternatives
Logseq is an open-source outliner application that makes it easy to write, organize and share your thoughts and to-do lists thanks to the ability to create and edit plain-text Markdown and Org-mode files. This means that your data is locally stored and yours forever and that it can be edited with any tools supporting those formats.
Obsidian vs. Roam vs. LogSeq: Which PKM App is Right For You?
While LogSeq and Roam function very similarly, LogSeq isn’t quite as refined. There’s a lot of thought that went into Roam’s simple interface, and while we appreciate that LogSeq is trying to push things forward in specific areas (like the addition of a Journals page), it doesn’t feel quite as smooth.

Social recommendations and mentions

Logseq might be a bit more popular than Jupyter. We know about 292 links to it since March 2021 and only 216 links to Jupyter. 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.

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 / 3 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 / 4 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 / 5 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 / 9 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 / 12 months ago
View more

Logseq mentions (292)

  • Show HN: Ephe – A Minimalist Open-Source Markdown Paper for Today
    I have been using Logseq [1] for this. It displays all days in a list view that you can scroll down, which I prefer. [1]: https://logseq.com/. - Source: Hacker News / 10 days ago
  • Ditching Obsidian and building my own
    I don't understand the negative concerns mentioned by the author. It's quite easy to sync notes to your mobile device using a free method, or using a cloud service you might already be paying for [4]. The great thing about Obsidian is that the notes itself are just markdown files, so you can use them in any other program. This protects you as a user in case Obsidian enters a enshittification phase. A good... - Source: Hacker News / 26 days ago
  • Why I switched from obsidian: A real developer’s story and what I’m using now
    Logseq Official Website A strong alternative if you love graph-based thinking. - Source: dev.to / about 1 month ago
  • Notetime: Minimalistic notes where everything is timestamped
    This idea feels a little like bullet journaling or logseq [0] to me. For what it's worth, I do this in Obsidian and clean-up my thoughts on a regular basis. It hits the right balance of minimalism and usefulness for me. 0: https://logseq.com/. - Source: Hacker News / 3 months ago
  • Dear (Rust) Devs: Article Request
    You want to build custom tooling or workflows in Logseq but you don't know Clojure (or Datalog, whatever that is). - Source: dev.to / 3 months ago
View more

What are some alternatives?

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

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.

Obsidian.md - A second brain, for you, forever. Obsidian is a powerful knowledge base that works on top of a local folder of plain text Markdown files.

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

Notion - All-in-one workspace. One tool for your whole team. Write, plan, and get organized.

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

Joplin - Joplin is a free, open source note taking and to-do application, which can handle a large number of notes organised into notebooks. The notes are searchable, tagged and modified either from the applications directly or from your own text editor.