Software Alternatives, Accelerators & Startups

Jupyter VS Jenkins

Compare Jupyter VS Jenkins 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.

Jenkins logo Jenkins

Jenkins is an open-source continuous integration server with 300+ plugins to support all kinds of software development
  • Jupyter Landing page
    Landing page //
    2023-06-22
  • Jenkins Landing page
    Landing page //
    2023-04-15

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.

Jenkins features and specs

  • Open Source
    Jenkins is an open-source tool, which means users can modify, share, and use it without licensing fees.
  • Large Plugin Ecosystem
    Jenkins has a robust plugin ecosystem with over 1,500 plugins, allowing extensive customization and functionality to fit various DevOps needs.
  • Active Community
    The active and large community of Jenkins users and developers provides extensive support, documentation, and shared solutions.
  • Platform Independent
    Jenkins can run on various platforms including Windows, macOS, and various Unix-like systems, providing flexibility in deployment.
  • CI/CD Capabilities
    Jenkins is well-suited for implementing Continuous Integration and Continuous Deployment (CI/CD) pipelines, facilitating automated build, test, and deployment processes.
  • Scalability
    It supports distributed builds using Master-Slave architecture, enabling you to scale your build and deployment processes across multiple machines.
  • Extensible
    Thanks to its plugin architecture, Jenkins can be extended to integrate with a variety of tools and services, making it highly adaptable.

Possible disadvantages of Jenkins

  • Complex Setup
    Initial setup and configuration of Jenkins can be complicated, especially for new users or large-scale environments.
  • Resource Intensive
    Jenkins can be resource-intensive, requiring significant memory and CPU, particularly for large projects or high-frequency builds.
  • Maintenance Overhead
    Due to its extensive plugin usage, keeping Jenkins and its plugins updated can be time-consuming and sometimes problematic.
  • Steep Learning Curve
    Learning to use Jenkins effectively can have a steep learning curve, particularly due to the need to understand its various plugins and configuration options.
  • User Interface
    The user interface of Jenkins is sometimes considered outdated and not as intuitive or user-friendly as some of its modern counterparts.
  • Security Vulnerabilities
    As with many open-source tools, Jenkins can have security vulnerabilities that need to be regularly addressed to ensure a secure environment.
  • Poor Plugin Compatibility
    Not all plugins are maintained equally, leading to potential compatibility issues or bugs when using multiple plugins together.

Jupyter videos

What is Jupyter Notebook?

More videos:

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

Jenkins videos

Mick Jenkins - The Circus Album Review | DEHH

More videos:

  • Review - Mick Jenkins - The Water[s] ALBUM REVIEW
  • Review - Mick Jenkins - THE WATERS First REACTION/REVIEW

Category Popularity

0-100% (relative to Jupyter and Jenkins)
Data Science And Machine Learning
DevOps Tools
0 0%
100% 100
Data Dashboard
100 100%
0% 0
Continuous Integration
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 Jenkins

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.

Jenkins Reviews

The Best Alternatives to Jenkins for Developers
Jenkins X, a new kind of Jenkins made for cloud environments and modern development practices, tries to make setting up and handling CI/CD pipelines easier. It uses Kubernetes along with GitOps ideas in order to offer teams working on cloud-native apps an automated way that is less complex when it comes to managing their project’s lifecycle.
Source: morninglif.com
Top 5 Jenkins Alternatives in 2024: Automation of IT Infrastructure Written by Uzair Ghalib on the 02nd Jan 2024
If you have searched about Jenkins alternatives and you are reading this article, then there must be one of the three reasons you are here. You are already using Jenkins and are fed up with facing different issues and looking for a change. Or maybe you haven’t faced any issues yet but have heard the stories about Jenkins issues and looking to avoid them by choosing an...
Source: attuneops.io
What Are The Best Alternatives To Ansible? | Attune, Jenkins &, etc.
Jenkin is a popular tool for performing continuous integration of software projects in the market. Plus, it continues the delivery of projects regardless of the platform you’re working on. And it is also responsible for handling any build or continuous integration with various testing and development technologies. As a product, Jenkins is more developer-centric and...
Best 8 Ansible Alternatives & equivalent in 2022
Jenkins is an open-source continuous integration tool. It is written using the Java programming language. It facilitates real-time testing and reporting on isolated changes in a larger code base. This software similar to Ansible helps developers to quickly find and solve defects in their code base & automate testing of their builds.
Source: www.guru99.com
Top 10 Most Popular Jenkins Alternatives for DevOps in 2024
Jenkins may be a de-facto tool for CI/CD, but it’s no longer a shiny newcomer borne directly out of modern DevOps best practices. Although Jenkins is still relevant, newer tools can offer improved ergonomics and expanded functionality. These can be better suited to contemporary software delivery methods.
Source: spacelift.io

Social recommendations and mentions

Based on our record, Jupyter seems to be a lot more popular than Jenkins. While we know about 216 links to Jupyter, we've tracked only 7 mentions of Jenkins. 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 / 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

Jenkins mentions (7)

  • CircleCI vs. Jenkins
    Jenkins is an open-source automation server used for software continuous integration and delivery. It automates various tasks, such as building, testing, and deploying applications.  It is easily extendable due to its vast ecosystem of plugins, making it easy to integrate into version control systems like Git, build tools like Maven/Gradle, and deployment platforms like AWS and Docker. - Source: dev.to / 3 months ago
  • Automated delivery React / Vue app for each Pull Request.
    It will give you a possibility to find and solve problems faster, release more stable and higher quality products. Here we will use CircleCI, but you can use whatever you need (Jenkins, Travis CI, GitLab CI). - Source: dev.to / about 1 year ago
  • Is Jenkins dead? v2
    CloudBees Jenkins Platform is a commercial offering from CloudBees, it is not the Jenkins project itself (which is open source). Jenkins is alive and well. See https://jenkins.io. Source: almost 2 years ago
  • ELI5 what is Jenkins?
    Ok. I'm talking about this: https://jenkins.io/. Source: over 2 years ago
  • I wanted a self hosted alternative to Atlassian status page so I build my own application !
    Currently supported : Datadog, Jenkins, DNS, HTTP. Source: over 2 years ago
View more

What are some alternatives?

When comparing Jupyter and Jenkins, 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.

CircleCI - CircleCI gives web developers powerful Continuous Integration and Deployment with easy setup and maintenance.

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

Codeship - Codeship is a fast and secure hosted Continuous Delivery platform that scales with your needs.

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

Travis CI - Simple, flexible, trustworthy CI/CD tools. Join hundreds of thousands who define tests and deployments in minutes, then scale up simply with parallel or multi-environment builds using Travis CI’s precision syntax—all with the developer in mind.