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Jupyter VS Heap

Compare Jupyter VS Heap and see what are their differences

LiveSession
LiveSession helps you analyze users’ behavior, improve UX, find JS bugs, and increase conversion rates using session replays, and event-based product analytics. featured
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Contents:
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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.

Heap logo Heap

Analytics for web and iOS. Heap automatically captures every user action in your app and lets you measure it all. Clicks, taps, swipes, form submissions, page views, and more.
  • Jupyter Landing page
    Landing page //
    2023-06-22
  • Heap Landing page
    Landing page //
    2023-10-05

Jupyter

Website
jupyter.org
Pricing URL
-
Release Date
-
Edit details

Heap

Website
heap.io
Pricing URL
Official Heap Pricing
Release Date
2013 January
Startup details
Country
United States
State
California
City
San Francisco
Founder(s)
Matin Movassate
Employees
100 - 249
Edit details

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.

Heap features and specs

  • Automatic Event Tracking
    Heap captures all user interactions automatically without requiring manual event setup, making it easier to get started and ensuring comprehensive data collection.
  • User-friendly Interface
    Heap provides a clean and intuitive interface, which allows non-technical users to easily create and analyze custom reports and dashboards.
  • Retroactive Analysis
    With Heap, users can define events at any time and view historical data, enabling analysis of past behaviors without prior configuration.
  • Comprehensive Data
    Heap collects a wide array of data points including clicks, form submissions, page views, and more, offering a holistic view of user interactions.
  • Integrations
    Heap offers robust integration capabilities with other analytics platforms, CRM systems, and data warehouses, facilitating seamless data flow between tools.

Possible disadvantages of Heap

  • Cost
    Heap can be expensive for smaller businesses or startups, particularly as the volume of tracked events and the number of users increases.
  • Learning Curve
    Despite its user-friendly interface, some users report a steep learning curve when it comes to leveraging Heap's more advanced features and capabilities.
  • Limited Customization
    While Heap provides a lot of data out-of-the-box, some users may find the customization options for tracking and reporting somewhat limited compared to other tools that offer more flexibility.
  • Data Redundancy
    The automatic tracking feature, while comprehensive, can sometimes lead to data redundancy or capturing irrelevant events, which may require additional data cleaning.
  • Reporting Complexity
    Some users have expressed that creating complex reports and funnels can be challenging and may require a deeper understanding of the platform's capabilities.

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

Heap videos

+ Add

Septimus Heap Series by Angie Sage || Spoiler Review

More videos:

  • Review - Fargo Season 1 Episode 8 "The Heap" Review
  • Review - Data Structures: Heaps

Category Popularity

0-100% (relative to Jupyter and Heap)

Jupyter

Heap

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Analytics
0 0%
Analytics
100% 100
Data Dashboard
100 100%
Data Dashboard
0% 0
Web Analytics
0 0%
Web Analytics
100% 100

User comments

Share your experience with using Jupyter and Heap. 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 Heap

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

Heap Reviews

10 Best Mixpanel Alternatives for Product Analytics in 2024
Heap is a web and mobile data analytics platform that captures every user interaction via secure session recording. Use it to get insights into customer behavior and to streamline your digital experiences. ⏩
Source: clickup.com
7 best Mixpanel alternatives to understand your users
On the other hand, Mixpanel requires you to manually define the events you want to track from the start. While this might take some extra time, it provides more detailed reports right off the bat, which makes the analysis straightforward. The choice between Heap and Mixpanel depends on whether you prioritize comprehensive data capturing (Heap) or a more detailed analysis...
Source: www.hotjar.com
Best Mixpanel Alternatives for SaaS
Heap is a robust product analytics platform that provides users with a plethora of in-depth insights into customer behavior and needs. With Heap, you can track user interactions in real time across all touch points within your product. Insights from Heap help you dig deeper into the paths users take when navigating your product and identify precise points of friction. Plus,...
Source: userpilot.com
Top 5 Plausible Analytics Alternatives in 2024
Additionally, Heap suggests reports for your review. You can define events, create segments, and utilize the event visualizer to delve into detailed user data.
Source: www.putler.com
Top 9 Plausible Analytics alternatives in 2024
Heap’s automatic event tracking and retroactive analytics offer a hassle-free approach, simplifying complex data analysis. Its user-friendly interface and intuitive tools enable effortless data exploration, offering detailed insights into user journeys without the need for manual tracking. Although it provides detailed user data, some users might find limitations in customer...
Source: usermaven.com

Social recommendations and mentions

Based on our record, Jupyter seems to be a lot more popular than Heap. While we know about 216 links to Jupyter, we've tracked only 11 mentions of Heap. 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

Heap mentions (11)

  • free-for.dev
    Heap.io — Automatically captures every user action in iOS or web apps. Free for up to 5,000 visits/month. - Source: dev.to / over 2 years ago
  • Question about testID in prod vs dev builds
    Check out Heap for React Native - https://heap.io. Source: over 2 years ago
  • All 2200+ companies in my db have a dedicated page now.
    How heavily does the site depend on heap.io for its core functionality? Like, say Heap went under completely out of the blue (god forbid) and you had to switch to Google analytics, how much tech debt are you in? Source: almost 3 years ago
  • Thousands of Popular Websites See What You Type–Before You Hit Submit
    Aren't services like Heap effectively worse versions of this? On their landing page they outright list this as their value prop: > Heap collects all the data on your customers - automatically. What they click. Where they go. What they do, even when you’re not looking. All without the need for engineers. [1]: https://heap.io/. - Source: Hacker News / about 3 years ago
  • We (Still) Believe in Private Offices (2015)
    Author here, surprising to see this blog post of mine trending, but it has held up pretty well! Happy to answer any questions about my time at Stack Overflow. I've since moved on to Heap (https://heap.io/) and we are hiring. We're virtual first so we don't have private offices, but we have the same values about treating developers well and giving them the space they need to do deep work. We're hiring for basically... - Source: Hacker News / over 3 years ago
View more

What are some alternatives?

When comparing Jupyter and Heap, 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.

Google Analytics - Improve your website to increase conversions, improve the user experience, and make more money using Google Analytics. Measure, understand and quantify engagement on your site with customized and in-depth reports.

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

Adobe Analytics - Adobe Analytics is an industry-leading solution that empowers you to understand your customers as people and steer your business with customer intelligence.

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

Mixpanel - Mixpanel is the most advanced analytics platform in the world for mobile & web.

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