Software Alternatives, Accelerators & Startups

Jupyter VS Microsoft Power BI

Compare Jupyter VS Microsoft Power BI and see what are their differences

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.

Microsoft Power BI logo Microsoft Power BI

BI visualization and reporting for desktop, web or mobile
  • Jupyter Landing page
    Landing page //
    2023-06-22
  • Microsoft Power BI Landing page
    Landing page //
    2023-06-14

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.

Microsoft Power BI features and specs

  • User-Friendly Interface
    Power BI has an intuitive drag-and-drop interface that makes it easy for users to create reports and dashboards without extensive technical knowledge.
  • Integration with Microsoft Products
    Seamlessly integrates with other Microsoft products like Excel, Azure, and Office 365, enhancing productivity and data accessibility.
  • Real-Time Data
    Supports real-time data streaming, which allows users to get up-to-date insights and make informed decisions quickly.
  • Custom Visualizations
    Offers a wide range of built-in visualizations, as well as the ability to create custom visuals, helping users present data in a meaningful way.
  • Robust Security
    Provides strong security features including role-based access, data encryption, and compliance with global regulatory standards.

Possible disadvantages of Microsoft Power BI

  • Complex Licensing
    The licensing model can be confusing and expensive, especially for small businesses or individual users.
  • Performance Issues with Large Data Sets
    Performance can be impacted when handling very large data sets, making it less suitable for extremely data-intensive applications.
  • Limited Customization
    While offering many built-in features, deep customization options may require advanced knowledge of DAX (Data Analysis Expressions) and Power Query.
  • Learning Curve
    Users new to business intelligence tools may find there is a significant learning curve to fully utilize all of Power BI's features.
  • Dependency on Internet Connection
    Many features, especially those involving cloud services, require a stable internet connection, which may be a limitation for some users.

Jupyter videos

What is Jupyter Notebook?

More videos:

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

Microsoft Power BI videos

No Microsoft Power BI videos yet. You could help us improve this page by suggesting one.

Add video

Category Popularity

0-100% (relative to Jupyter and Microsoft Power BI)
Data Science And Machine Learning
Data Dashboard
20 20%
80% 80
Data Visualization
0 0%
100% 100
Database Tools
100 100%
0% 0

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 Microsoft Power BI

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.

Microsoft Power BI Reviews

Explore 7 Tableau Alternatives for Data Visualization and Analysis
Microsoft Power BI is a robust data visualization and business intelligence tool that enables users to create interactive, real-time dashboards and reports with minimal coding. It supports over 100 data connectors, integrates seamlessly with the Azure SQL Database, and features advanced data modeling with the DAX language. Power BI's intuitive interface, frequent AI-driven...
Source: www.draxlr.com
Explore 6 Metabase Alternatives for Data Visualization and Analysis
It offers multiple pricing options, including a free version for individual users and paid plans like Power BI Pro and Power BI Premium. Pricing is based on user and capacity needs.
Source: www.draxlr.com
5 best Looker alternatives
Power BI: Microsoft Power BI is a legacy BI tool that is known for its seamless integration to Microsoft ecosystem, which is one of its strongest advantages. However, this tight integration can also be a drawback, as it tends to have limited compatibility with other ecosystems and often relies on Microsoft tools for optimal functionality.
Source: www.draxlr.com
10 Best Alternatives to Looker in 2024
Power BI: Microsoft's Power BI stands out for its seamless integration with other Microsoft products, making it a top choice for organizations deeply invested in the Microsoft ecosystem. Its powerful data visualization tools and extensive community support make it a strong contender in the BI landscape.
Top 10 AI Data Analysis Tools in 2024
Microsoft Power BI is a versatile business intelligence platform that enables users to sort through their data and visualize it for actionable insights. One of its key strengths lies in its ability to import data from nearly any source, allowing users to build reports and dashboards effortlessly. Additionally, Power BI empowers users to build machine learning models and...
Source: powerdrill.ai

Social recommendations and mentions

Based on our record, Jupyter seems to be a lot more popular than Microsoft Power BI. While we know about 216 links to Jupyter, we've tracked only 17 mentions of Microsoft Power BI. 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 / about 1 month 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

Microsoft Power BI mentions (17)

  • Unified Analytics Platform: Microsoft Fabric
    Microsoft Fabric is currently in preview and provides data integration, engineering, data warehousing, data science, real-time analytics, applied observability, and business intelligence under a single architecture by integrating services such as Azure Data Factory, Azure Synapse Analytics, Data Activator, and Power BI. In addition, it comes with a SaaS, multi-cloud data lake called "OneLake" that is built-in and... Source: almost 2 years ago
  • NSS Data Analytics Program Question
    I'd suggest spending some time learning the material before you invest thousands in tuition only to find that you don't like it or aren't good at it. Download Tableau Public or Power BI and force yourself to use them for a few months. That's how I taught myself R. Source: about 2 years ago
  • Why Is Data Analytics Important?
    Discover why business analytics is crucial for your business and how to utilise data analytics and PowerBI to make informed and data-backed decisions! Source: about 2 years ago
  • Cloud dB reporting tool?
    Power BI is popular... But for table reports with Excel/PDF export you can use Pebble Reports. Source: about 2 years ago
  • Asking for guidance on migrating to a database from Excel
    Yes, MySQL can do the job. You can use Airforms to do data entry. No need to learn MySQL syntax. You will also need a reporting tool, such as Power BI. Source: about 2 years ago
View more

What are some alternatives?

When comparing Jupyter and Microsoft Power BI, 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.

Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

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

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

Sisense - The BI & Dashboard Software to handle multiple, large data sets.

Presto DB - Distributed SQL Query Engine for Big Data (by Facebook)