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Make.com VS Jupyter

Compare Make.com VS Jupyter and see what are their differences

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All-in-one work management platform for team collaboration. featured
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Make.com logo Make.com

Tool for workflow automation (Former Integromat)

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.
  • Make.com Landing page
    Landing page //
    2022-07-05
  • Jupyter Landing page
    Landing page //
    2023-06-22

Make.com features and specs

  • Ease of Use
    Make.com offers a user-friendly interface with drag-and-drop functionality, making it accessible for non-technical users.
  • Integration Options
    The platform supports a wide array of integrations with popular apps and services, enabling complex workflows.
  • Custom Workflows
    Users can create highly customized workflows tailored to specific business needs, allowing for greater flexibility.
  • Scalability
    Make.com is built to handle both small-scale and enterprise-level tasks, providing a scalable solution as your business grows.
  • Community and Support
    There is an active community and comprehensive support, including documentation and forums, to help users troubleshoot and optimize their usage.
  • Real-time Monitoring and Analytics
    The platform offers real-time monitoring and analytics, allowing users to track the performance of their workflows and make data-driven decisions.
  • Versatile Triggers and Actions
    Make.com offers a variety of triggers and actions that can be used to automate a wide range of tasks across different services.

Possible disadvantages of Make.com

  • Pricing
    The pricing structure can be expensive for small businesses or individual users, especially for advanced features and high-volume usage.
  • Learning Curve
    Despite its user-friendly design, there is still a learning curve for newcomers to understand all the capabilities and features.
  • Occasional Bugs
    Users have reported occasional bugs and issues, which can disrupt workflows and require troubleshooting.
  • Limited Offline Support
    Make.com heavily relies on internet connectivity, which can be a drawback for users requiring offline functionality.
  • Complexity for Advanced Features
    While basic workflows are easy to set up, leveraging more advanced features may require a deeper understanding of the platform and potentially some coding knowledge.
  • Dependency on Third-party Services
    The platform’s effectiveness is influenced by the reliability and performance of third-party services it integrates with, making it susceptible to external issues.
  • Data Privacy Concerns
    Storing and processing data through third-party services may raise privacy and compliance issues for businesses dealing with sensitive information.

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.

Analysis of Make.com

Overall verdict

  • Overall, Make.com is considered a good platform for those looking to streamline processes and improve efficiency through automation. Its flexible and powerful features cater to a wide range of needs, although there may be a learning curve for those new to automation or with limited technical knowledge.

Why this product is good

  • Make.com, formerly known as Integromat, is a popular platform for automating workflows and integrating various software tools. It offers a visual interface that allows users to connect different applications and automate repetitive tasks, enhancing productivity. Its ability to create complex multi-step automations with various conditions and triggers makes it a robust tool for both small businesses and larger enterprises.

Recommended for

  • small business owners
  • project managers
  • IT professionals
  • digital marketers
  • anyone looking to automate tasks without extensive coding knowledge

Make.com videos

+ Add

Zapier vs Integromat - Quick Comparison Review

More videos:

  • Review - Integromat feature tour
  • Review - Introduction to Integromat

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 Make.com and Jupyter)

Make.com

Jupyter

Automation
100 100%
Automation
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Web Service Automation
100 100%
Web Service Automation
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100

User comments

Share your experience with using Make.com 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 Make.com and Jupyter

Make.com Reviews

The Best n8n.io Alternatives for Workflow Automation in 2025
Make, formerly known as Integromat, is a versatile no-code platform that enables users to create sophisticated workflows with ease. It offers a visual workflow builder that allows users to connect various applications and services, define conditional logic, and manipulate data without writing any code. Make's strengths lie in its ability to handle complex workflows and its...
Source: latenode.com
N8n.io Alternatives
One of the standout features of Integromat is its flexibility and customization options. Users can set up multi-step workflows with conditional logic, ensuring that each automation is tailored to their specific needs. Additionally, Integromat offers advanced error handling and data manipulation capabilities, providing robust solutions for complex automation requirements. For...
Source: apix-drive.com
The Best MuleSoft Alternatives [2024]
Make (formerly Integromat) is an integration solution that allows you to automate and connect applications, databases, web services, chatbots, and other systems.
Source: exalate.com
Top 9 MuleSoft Alternatives & Competitors in 2024
Make, one of the best Mulesoft alternatives, the ultimate IT process automation tool for enhancing efficiency, productivity, and collaboration. By automating routine tasks, integrating with existing infrastructure, and offering powerful workflow automation, Make empowers your team to streamline processes and achieve remarkable results.
Source: www.zluri.com
Zapier vs. Make.com: Which Automation Tool Will Take the Business Lead?
Make.com offers a cost-effective option for those looking for a business process automation solution, even if it may compromise usability and integration. From your scenario, Make.com seems like a realistic alternative for those with a more limited budget or those willing to work with additional API documentation and webhooks instead of the broader integration that Zapier...
Source: www.listproductsreview.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

Based on our record, Jupyter seems to be more popular. It has been mentiond 216 times since March 2021. 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.

Make.com mentions (0)

We have not tracked any mentions of Make.com yet. Tracking of Make.com recommendations started around Mar 2021.

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 / 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
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What are some alternatives?

When comparing Make.com and Jupyter, you can also consider the following products

Zapier - Connect the apps you use everyday to automate your work and be more productive. 1000+ apps and easy integrations - get started in minutes.

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.

ifttt - IFTTT puts the internet to work for you. Create simple connections between the products you use every day.

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

n8n.io - Free and open fair-code licensed node based Workflow Automation Tool. Easily automate tasks across different services.

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

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