Jupyter Notebook vs. MATLAB

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Jupyter Notebook
Score 8.8 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
MATLAB
Score 8.3 out of 10
N/A
MatLab is a predictive analytics and computing platform based on a proprietary programming language. MatLab is used across industry and academia.
$49
per student license
Pricing
Jupyter NotebookMATLAB
Editions & Modules
No answers on this topic
Student
$49
per student license
Student
$49
per student suite license
Home
$149
perpetual license
Education
$250
per year
Education
$500
perpetual license
Standard
$860
per year
Standard
2,150
perpetual license
Offerings
Pricing Offerings
Jupyter NotebookMATLAB
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Jupyter NotebookMATLAB
Considered Both Products
Jupyter Notebook
MATLAB

No answer on this topic

Top Pros
Top Cons
Features
Jupyter NotebookMATLAB
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Jupyter Notebook
8.5
21 Ratings
0% above category average
MATLAB
-
Ratings
Connect to Multiple Data Sources9.021 Ratings00 Ratings
Extend Existing Data Sources9.220 Ratings00 Ratings
Automatic Data Format Detection8.514 Ratings00 Ratings
MDM Integration7.415 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Jupyter Notebook
9.6
21 Ratings
13% above category average
MATLAB
-
Ratings
Visualization9.621 Ratings00 Ratings
Interactive Data Analysis9.621 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Jupyter Notebook
9.0
21 Ratings
9% above category average
MATLAB
-
Ratings
Interactive Data Cleaning and Enrichment9.320 Ratings00 Ratings
Data Transformations8.921 Ratings00 Ratings
Data Encryption8.514 Ratings00 Ratings
Built-in Processors9.314 Ratings00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Jupyter Notebook
8.9
21 Ratings
5% above category average
MATLAB
-
Ratings
Multiple Model Development Languages and Tools9.020 Ratings00 Ratings
Automated Machine Learning9.218 Ratings00 Ratings
Single platform for multiple model development9.221 Ratings00 Ratings
Self-Service Model Delivery8.020 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Jupyter Notebook
8.8
19 Ratings
3% above category average
MATLAB
-
Ratings
Flexible Model Publishing Options8.819 Ratings00 Ratings
Security, Governance, and Cost Controls8.718 Ratings00 Ratings
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Jupyter NotebookMATLAB
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All AlternativesView all alternativesView all alternatives
User Ratings
Jupyter NotebookMATLAB
Likelihood to Recommend
8.4
(22 ratings)
8.1
(53 ratings)
Usability
10.0
(1 ratings)
9.9
(4 ratings)
Support Rating
9.0
(1 ratings)
9.5
(7 ratings)
User Testimonials
Jupyter NotebookMATLAB
Likelihood to Recommend
Open Source
I've created a number of daisy chain notebooks for different workflows, and every time, I create my workflows with other users in mind. Jupiter Notebook makes it very easy for me to outline my thought process in as granular a way as I want without using innumerable small. inline comments.
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MathWorks
MATLAB really does best for solving computational problems in math and engineering. Especially when you have to use a lot of functions in your solving process, or if you have a nonlinear equation that must be iteratively solved. [MATLAB] can also perform things like integration and derivation on your equations that you put into it.
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Pros
Open Source
  • Simple and elegant code writing ability. Easier to understand the code that way.
  • The ability to see the output after each step.
  • The ability to use ton of library functions in Python.
  • Easy-user friendly interface.
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MathWorks
  • It has a very user friendly library which helps users learn this software fairly quickly in a short span of time.
  • The graphical user interface provided by the software is really good.
  • The code that a person writes allows options for debugging.
  • One can visualize the flow of control of their code inside MATLAB.
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Cons
Open Source
  • 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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MathWorks
  • MatLab is pricier than most of its competitors and because of this reason, many organizations are moving towards cheaper alternatives - mostly Python.
  • MatLab is inefficient when it comes to performing a large number of iterations. It gets laggy and often crashes. Python is better in this regard.
  • There is a limited number of hardware options (mostly NI) that can be connected directly to the data acquisition toolbox.
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Usability
Open Source
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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MathWorks
MATLAB is pretty easy to use. You can extend its capabilities using the programming interface. Very flexible capabilities when it comes to graphical presentation of your data (so many different kinds of options for your plotting needs). Anytime you are working with large data sets, or with matrices, MATLAB is likely to be very helpful.
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Support Rating
Open Source
I haven't had a need to contact support. However, all required help is out there in public forums.
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MathWorks
The built-in search engine is not as performing as I wish it would be. However, the YouTube channel has a vast library of informative video that can help understanding the software. Also, many other software have a nice bridge into MATLAB, which makes it very versatile. Overall, the support for MATLAB is good.
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Alternatives Considered
Open Source
With Jupyter Notebook besides doing data analysis and performing complex visualizations you can also write machine learning algorithms with a long list of libraries that it supports. You can make better predictions, observations etc. with it which can help you achieve better business decisions and save cost to the company. It stacks up better as we know Python is more widely used than R in the industry and can be learnt easily. Unlike PyCharm jupyter notebooks can be used to make documentations and exported in a variety of formats.
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MathWorks
How MATLAB compares to its competition or similar open access tools like R (programming language) or SciLab is that it's simply more powerful and capable. It embraces a wider spectrum of possibilities for far more fields than any other environment. R, for example, is intended primarily for the area of statistical computing. SciLab, on the other hand, is a similar open access tool that falls very short in its computing capabilities. It's much slower when running larger scripts and isn't documented or supported nearly as well as MATLAB.
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Return on Investment
Open Source
  • 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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MathWorks
  • MATLAB helps us quickly sort through large sets of data because we keep the same script each time we run an analyzation, making it very efficient to run this whole process.
  • The software makes it super easy for us to create plots that we can then show to investors or clients to display our data.
  • We are also looking to create an app for our product, and we will not be able to do that on MATLAB, therefore creating a limiting issue and a new learning curve for a programming language.
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