Jupyter Notebook vs. Wolfram Mathematica

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Jupyter Notebook
Score 9.4 out of 10
N/A
Jupyter Notebook is an open-source web application that allows users to create and share documents containing live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, and machine learning. It supports over 40 programming languages, and notebooks can be shared with others using email, Dropbox, GitHub and the Jupyter Notebook Viewer. It is used with JupyterLab, a web-based IDE for…N/A
Mathematica
Score 8.2 out of 10
N/A
Wolfram's flagship product Mathematica is a modern technical computing application featuring a flexible symbolic coding language and a wide array of graphing and data visualization capabilities.
$1,520
per year
Pricing
Jupyter NotebookWolfram Mathematica
Editions & Modules
No answers on this topic
Standard Cloud
$1,520
per year
Standard Desktop
$3,040
one-time fee
Standard Desktop & Cloud
$3,344
one-time fee
Mathematica Enterprise Edition
$8,150.00
one-time fee
Offerings
Pricing Offerings
Jupyter NotebookMathematica
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsDiscounts available for students and educational institutions. The Network Edition reduce per-user license costs through shared deployment across any number of machines on a local-area network.
More Pricing Information
Community Pulse
Jupyter NotebookWolfram Mathematica
Features
Jupyter NotebookWolfram Mathematica
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Jupyter Notebook
9.0
Ratings
7% above category average
Wolfram Mathematica
-
Ratings
Connect to Multiple Data Sources10.00 Ratings00 Ratings
Extend Existing Data Sources10.00 Ratings00 Ratings
Automatic Data Format Detection8.50 Ratings00 Ratings
MDM Integration7.40 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Jupyter Notebook
7.0
Ratings
18% below category average
Wolfram Mathematica
-
Ratings
Visualization6.00 Ratings00 Ratings
Interactive Data Analysis8.00 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Jupyter Notebook
9.5
Ratings
15% above category average
Wolfram Mathematica
-
Ratings
Interactive Data Cleaning and Enrichment10.00 Ratings00 Ratings
Data Transformations10.00 Ratings00 Ratings
Data Encryption8.50 Ratings00 Ratings
Built-in Processors9.30 Ratings00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Jupyter Notebook
9.3
Ratings
10% above category average
Wolfram Mathematica
-
Ratings
Multiple Model Development Languages and Tools10.00 Ratings00 Ratings
Automated Machine Learning9.20 Ratings00 Ratings
Single platform for multiple model development10.00 Ratings00 Ratings
Self-Service Model Delivery8.00 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Jupyter Notebook
10.0
Ratings
16% above category average
Wolfram Mathematica
-
Ratings
Flexible Model Publishing Options10.00 Ratings00 Ratings
Security, Governance, and Cost Controls10.00 Ratings00 Ratings
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Jupyter Notebook
-
Ratings
Wolfram Mathematica
9.9
Ratings
16% above category average
Pixel Perfect reports00 Ratings9.80 Ratings
Customizable dashboards00 Ratings9.90 Ratings
Report Formatting Templates00 Ratings9.90 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Jupyter Notebook
-
Ratings
Wolfram Mathematica
9.9
Ratings
22% above category average
Drill-down analysis00 Ratings9.90 Ratings
Formatting capabilities00 Ratings9.90 Ratings
Integration with R or other statistical packages00 Ratings9.90 Ratings
Report sharing and collaboration00 Ratings9.90 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Jupyter Notebook
-
Ratings
Wolfram Mathematica
9.3
Ratings
10% above category average
Publish to Web00 Ratings9.90 Ratings
Publish to PDF00 Ratings9.00 Ratings
Report Versioning00 Ratings9.90 Ratings
Report Delivery Scheduling00 Ratings8.90 Ratings
Delivery to Remote Servers00 Ratings8.90 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
Jupyter Notebook
-
Ratings
Wolfram Mathematica
9.9
Ratings
20% above category average
Pre-built visualization formats (heatmaps, scatter plots etc.)00 Ratings9.90 Ratings
Location Analytics / Geographic Visualization00 Ratings9.90 Ratings
Predictive Analytics00 Ratings9.90 Ratings
Best Alternatives
Jupyter NotebookWolfram Mathematica
Small Businesses
IBM Watson Studio
IBM Watson Studio
Score 10.0 out of 10
Supermetrics
Supermetrics
Score 10.0 out of 10
Medium-sized Companies
Posit
Posit
Score 10.0 out of 10
Supermetrics
Supermetrics
Score 10.0 out of 10
Enterprises
Posit
Posit
Score 10.0 out of 10
Dataiku
Dataiku
Score 7.6 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Jupyter NotebookWolfram Mathematica
Likelihood to Recommend
10.0
(0 ratings)
9.9
(0 ratings)
Usability
10.0
(0 ratings)
-
(0 ratings)
Support Rating
9.0
(0 ratings)
9.5
(0 ratings)
User Testimonials
Jupyter NotebookWolfram Mathematica
Likelihood to Recommend
I would rate it 9/10 while recommending Jupyter Notebook as it offers me a wide range of functionality to operate. It is very well suited for someone who is new to python programming as the user interface helps you build code line by line. I personally have written multiple programs in Python using Jupyter Notebook as it helps me organize long code by breaking it in a structure. Also the ability to write comments using '#' helps a lot to a reader understand the code.
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We are the judgement that Wolfram Mathematica is despite many critics based on the paradigms selected a mark in the fields of the markets for computations of all kind. Wolfram Mathematica is even a choice in fields where other bolide systems reign most of the market. Wolfram Mathematica offers rich flexibility and internally standardizes the right methodologies for his user community. Wolfram Mathematica is not cheap and in need of a hard an long learner journey. That makes it weak in comparison with of-the-shelf-solution packages or even other programming languages. But for systematization of methods Wolfram Mathematica is far in front of almost all the other. Scientist and interested people are able to develop themself further and Wolfram Matheamatica users are a human variant for themself. The reach out for modern mathematics based science is deep and a unique unified framework makes the whole field of mathematics accessable comparable to the brain of Albert Einstein. The paradigms incorporated are the most efficients and consist in assembly on the market. The mathematics is covering and fullfills not just education requirements but the demands and needs of experts.
Mathematica is incompatible with other systems for mCAx and therefore the borders between the systems are hard to overcome. Wolfram Mathematica should be consider one of the more open systems because other code can be imported and run but on the export side it is rathe incompatible by design purposes. A better standard for all that might solve the crisis but there is none in sight. Selection of knowledge of what works will be in the future even more focussed and general system might be one the lossy side. Knowledge of esthetics of what will be in the highest demand in necessary and Wolfram is not a leader in this field of science. Mathematics leves from gathering problems from application fields and less from the glory of itself and the formalization of this.
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Pros
  • Coding and error correction line by line
  • Simple and Effectiveness
  • Easy to use for visualisation and presentation of code
  • Could be used at any place any time without hassle
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  • Doing the analysis is very good, plotting the data, getting the insight from data using this is easy and output looks pretty good
  • Solving mathematical problems, with detailed solutions step by step (mainly calculus problems)
  • You can also query this knowledge engine in simple English. It has ability to interpret that and will give you answer accordingly
  • Nowadays, it provides API to use, so you can do image processing, video/audio using this
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Cons
  • Need more Hotkeys for creating a beautiful notebook. Sometimes we need to download other plugins which messes [with] its default settings.
  • Not as powerful as IDE, which sometimes makes [the] job difficult and allows duplicate code as it get confusing when the number of lines increases. Need a feature where [an] error comes if duplicate code is found or [if a] developer tries the same function name.
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  • Should include more libraries and functions.
  • Should include more functions that can be used in Machine Learning.
  • Should include more functions that can be used in Data Science.
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Usability
Jupyter is highly simplistic. It took me about 5 mins to install and create my first "hello world" without having to look for help. The UI has minimalist options and is quite intuitive for anyone to become a pro in no time. The lightweight nature makes it even more likeable.
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No answers on this topic
Support Rating
I haven't had a need to contact support. However, all required help is out there in public forums.
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Wolfram Mathematica is a nice software package. It has very nice features and easy to install and use in your machine. Besides this, there is a nice support from Wolfram. They come to the university frequently to give seminars in Mathematica. I think this is the best thing they are doing. That is very helpful for graduate and undergraduate students who are using Mathematica in their research.
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Alternatives Considered
Jupyter Notebook is unique in that it offers a flexible, lightweight, easy-to-replicate way of organizing your code in a visually intuitive fashion that can be exported in a number of formats. I've found that the broad functionalities available within the notebooks suit a lot of needs I have for EDA, modeling, and data export that makes other software products fairly redundant.
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The ability to manipulate algebraic expressions, nested lists, and data structures in Mathematica was unequalled when I first did the comparison. Since then, I've stuck with Mathematica mostly because it's "the tool I know."
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Return on Investment
  • Positive impact: flexible implementation on any OS, for many common software languages
  • Positive impact: straightforward duplication for adaptation of workflows for other projects
  • Negative impact: sometimes encourages pigeonholing of data science work into notebooks versus extending code capability into software integration
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  • Mathematica is our "go to" environment for developing solutions for our clients, so I suppose you could say that it is solely responsible for our revenues. On occasion we do use other platforms but Mathematica is a core component of our offer to clients.
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