Software Alternatives, Accelerators & Startups

Jupyter VS Archbee.io

Compare Jupyter VS Archbee.io and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

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.

Archbee.io logo Archbee.io

Archbee is a developer-focused product docs tool for your team. Build beautiful product documentation sites or internal wikis/knowledge bases to get your team and product knowledge in one place.
  • Jupyter Landing page
    Landing page //
    2023-06-22
  • Archbee.io Landing page
    Landing page //
    2021-08-30

Write in a blazingly fast WYSIWYG editor with 30+ custom blocks and native markdown to create built-in diagrams, API docs, Swagger, GraphQL. Check the out of the box integrations with Github, Slack, Lucidchart, Airtable, Google Sheets, Typeform, Jira, or Figma. Inline comments for async collaboration and to enhance team performance or minimize knowledge churn are supported by Archbee's collaborative features.

Why Archbee?

  • Focused on engineering people’s needs.
  • Integrated CMS & hosting platform for docs to allow easy internal and external access.
  • One-click hosting with SEO support and layout templates.
  • Reduce knowledge churn and become remote-friendly.
  • Improve onboarding time and increase developer efficiency.

Effortless content editing and collaboration

  • 20+ Custom Blocks
  • Inline Comments
  • Links & Mentions
  • Markdown editing

Say goodbye to the slow and clunky

  • Drag & Drop to Organize
  • Flexible & Powerful Search
  • Infinite History
  • Access Control
  • Knowledge Graph

Archbee.io

$ Details
freemium $30.0 / Monthly (5 users)
Platforms
Browser Windows Mac OSX Linux
Release Date
2019 May

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.

Archbee.io features and specs

  • CDN & Image Optimization on your custom domains
  • Custom JavaScript
  • Custom CSS
  • Search Analytics for team and customer queries
  • JWT authentication for shared collections

Jupyter videos

What is Jupyter Notebook?

More videos:

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

Archbee.io videos

Archbee.io Review- My Honest Opinion

More videos:

  • Demo - Archbee walkthrough

Category Popularity

0-100% (relative to Jupyter and Archbee.io)
Data Science And Machine Learning
Documentation
0 0%
100% 100
Data Dashboard
100 100%
0% 0
Developer Tools
0 0%
100% 100

User comments

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Reviews

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

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.

Archbee.io Reviews

Best Gitbook Alternatives You Need to Try in 2023
One alternative to Gitbook is Archbee. A powerful platform that allows users to write, collaborate and publish self-service knowledge portals quickly. One of the main advantages of using Archbee is its simplicity combined with advanced documentation capabilities.
Source: www.archbee.com
12 Most Useful Knowledge Management Tools for Your Business
Archbee offers Mermaid, as well as Markdown through GitHub, and API capabilities, meaning it’s perfect for code documentation. In addition, 30+ custom blocks, as well as 25 embeds and integrations available, make this tool extremely versatile, covering most documentation needs.
Source: www.archbee.com

Social recommendations and mentions

Based on our record, Jupyter seems to be a lot more popular than Archbee.io. While we know about 216 links to Jupyter, we've tracked only 21 mentions of Archbee.io. 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 / 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 / 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 / 11 months ago
View more

Archbee.io mentions (21)

  • How to simplify, self-contain and delegate work?
    If you have a tech business, you should look into an internal knowledge base that is aligned with developers. archbee.com is similar to document360, but with features that are relevant to write developer documentation, APIs etc. Source: almost 3 years ago
  • Best tool for creating GraphQL API documentation?
    But if you want something similar with your example, check archbee.com, it has integration with GraphiQL. Source: almost 3 years ago
  • How can I make API docs?
    If you want to get a tool and don't need to start building your own setup I would recommend looking into some documentation platforms like archbee.io. Source: almost 3 years ago
  • End user documentation tools - knowledge base / manual
    If you want to go with a SaaS, I'd say to check archbee.io - because you can do end user guides and developer documentation... Source: almost 3 years ago
  • What's your documentation stack?
    It's hard to enforce developers to update documentation. Ideally, you should have somebody responsible to do it. As for the documentation stack, archbee.io for both internal and external. A good alternative to Notion since it supports markdown, code blocks with more options and API references. Source: almost 3 years ago
View more

What are some alternatives?

When comparing Jupyter and Archbee.io, 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.

ReadMe - A collaborative developer hub for your API or code.

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

Slite - Your company knowledge

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

GitBook - Modern Publishing, Simply taking your books from ideas to finished, polished books.