Anaconda is an enterprise Python platform that provides access to open-source Python and R packages used in AI, data science, and machine learning. These enterprise-grade solutions are used by corporate, research, and academic institutions for competitive advantage and research.
$0
per month
MATLAB
Score 8.8 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
SharePoint
Score 7.7 out of 10
N/A
Microsoft's SharePoint is an Intranet solution that enables users to share and manage content, knowledge, and applications to empower teamwork, quickly find information, and collaborate across the organization.
$5
Per User Per Month
Pricing
Anaconda
MATLAB
Microsoft SharePoint
Editions & Modules
Free Tier
$0
per month
Starter Tier
$15
per month per user
Business
$50
per month per user
Custom
Contact Sales
Student
$49
per student license
Home
$149
perpetual license
Education
$250
per year
Education
$500
perpetual license
Standard
$860
per year
Standard
2,150
perpetual license
Plan 1
$5.00
Per User Per Month
Plan 2
$10.00
Per User Per Month
Office 365 E3
$20.00
Per User Per Month
Offerings
Pricing Offerings
Anaconda
MATLAB
SharePoint
Free Trial
No
No
Yes
Free/Freemium Version
Yes
No
No
Premium Consulting/Integration Services
Yes
No
No
Entry-level Setup Fee
No setup fee
No setup fee
No setup fee
Additional Details
Users within organizations with 200+ employees/contractors (including Affiliates) require a paid Business license. Academic and non-profit research institutions may qualify for exemptions.
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More Pricing Information
Community Pulse
Anaconda
MATLAB
Microsoft SharePoint
Considered Multiple Products
Anaconda
Verified User
Engineer
Chose Anaconda
It provides several IDEs like Spyder and Jupiter that would be enough for me to write my Python script. You can easily install it on a Windows or Linux computer and supports many libraries.
Anaconda is the best Python environment because you have all the things you need all in one places, at the reach of your hand. You can download and manage libraries as you wish and is very easy to create new projects and API's for all your stuff.
Matlab is faster, more complete, easier to use and with better documentation comparing with the previously mentioned programs. I haven't used Anaconda that much, but I felt more comfortable with Matlab rather than using Python for this project specifically. Its coding language …
MATLAB's neurophysiological data pre-processing third-party packages are more scientifically validated compared to support for other software platforms. It also allows for writing code with a greater level of functionality and more capabilities than R-Studio, which is instead …
Apart from Matlab, I used Matematica for some of my integral evaluations. Mathematica is also a "clean" and easy-to-use software that solves symbolic math problems (even better than Matlab for symbolic math). I also used Anaconda and Spyder for my career so far.
I selected MATLAB against the other programs because it has a very powerful console and a very simple way to program functions and scripts, instead of having to make a whole project and loose a lot of time performing things that MATLAB make ir for you.
I have asked all my juniors to work with Anaconda and Pycharm only, as this is the best combination for now. Coming to use cases: 1. When you have multiple applications using multiple Python variants, it is a really good tool instead of Venv (I never like it). 2. If you have to work on multiple tools and you are someone who needs to work on data analytics, development, and machine learning, this is good. 3. If you have to work with both R and Python, then also this is a good tool, and it provides support for both.
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.
SharePoint Document Management excels as a central repository for storing, organising, and retrieving documents. It supports version control, metadata tagging, secure access, and integration with tools like Power Automate. At our organisation, it's used for managing contracts, policies, and supplier documents. SharePoint Workflow Automation integrates with Power Automate to streamline approvals, gather feedback, and automate recurring tasks. This reduces reliance on email chains and manual trackers.
Anaconda is a one-stop destination for important data science and programming tools such as Jupyter, Spider, R etc.
Anaconda command prompt gave flexibility to use and install multiple libraries in Python easily.
Jupyter Notebook, a famous Anaconda product is still one of the best and easy to use product for students like me out there who want to practice coding without spending too much money.
I used R Studio for building Machine Learning models, Many times when I tried to run the entire code together the software would crash. It would lead to loss of data and changes I made.
Windows Explorer users have some difficulty having to constantly UPLOAD / DOWNLOAD files. Specifically on the DOWNLOAD when they are used to Drag & Drop in & out of LOCAL folders via Window's explorer.
Microsoft SharePoint supports multiple "library" types. When implementing our "image" library the search function is done via "tags" and boolean logic. This is challenging to most end users. I'd like our users to be able to search our Microsoft SharePoint image library without having to enter KEYWORD or other BOOLEAN logic.
Microsoft SharePoint can also be an internal website for each department or company wide communication tool but I believe these features are geared for much larger organizations. Since we are a SMB we really aren't using these features. So maybe something more useful to SMBs would be nice.
It's really good at data processing, but needs to grow more in publishing in a way that a non-programmer can interact with. It also introduces confusion for programmers that are familiar with normal Python processes which are slightly different in Anaconda such as virtualenvs.
It's integral to our business. It's already included with most of the Office 365 licensing we buy, so the cost is effectively zero. It stores our files, it is the foundation for custom applications, and Microsoft only continues to enhance its functionality and its connections to other Microsoft tools. SharePoint just keeps getting better and better.
I am giving this rating because I have been using this tool since 2017, and I was in college at that time. Initially, I hesitated to use it as I was not very aware of the workings of Python and how difficult it is to manage its dependency from project to project. Anaconda really helped me with that. The first machine-learning model that I deployed on the Live server was with Anaconda only. It was so managed that I only installed libraries from the requirement.txt file, and it started working. There was no need to manually install cuda or tensor flow as it was a very difficult job at that time. Graphical data modeling also provides tools for it, and they can be easily saved to the system and used anywhere.
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.
No usability issues reported. Individual teams also have allocated areas which replace legacy shared drives on local LANs. Access to Sharepoint resources is fully integrated with corporate Active Directory with additional two-factor authentication required for administrative users. Users have access to Microsoft Services Hub which allows you to create, manage, and track support requests while staying current on Microsoft technologies with access to select self-paced learning paths
Anaconda provides fast support, and a large number of users moderate its online community. This enables any questions you may have to be answered in a timely fashion, regardless of the topic. The fact that it is based in a Python environment only adds to the size of the online community.
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.
The face to face training I received was on SharePoint Administration. It was rushed as there was a lot of information to cover and the application of the labs weren't that great either. I like to be able to relate what I am learning to what I am currently doing.
I like to learn at my own pace and online training allows for that. Additionally, you can skip through pieces of content that you already know or are already comfortable with. Microsoft actually offers great videos on their website for basic fundamental SharePoint Training. I have used these training videos in some of my own training sessions with end users.
I have experience using RStudio oustide of Anaconda. RStudio can be installed via anaconda, but I like to use RStudio separate from Anaconda when I am worin in R. I tend to use Anaconda for python and RStudio for working in R. Although installing libraries and packages can sometimes be tricky with both RStudio and Anaconda, I like installing R packages via RStudio. However, for anything python-related, Anaconda is my go to!
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.
The reasons for selecting MS SharePoint are: SharePoint provides ease of use and web design assistance and support SharePoint helps you schedule your content for publishing. enables users to share documents with external parties and offers a better internal structure of the content and better indexing and searching capabilities.
It has helped our organization to work collectively faster by using Anaconda's collaborative capabilities and adding other collaboration tools over.
By having an easy access and immediate use of libraries, developing times has decreased more than 20 %
There's an enormous data scientist shortage. Since Anaconda is very easy to use, we have to be able to convert several professionals into the data scientist. This is especially true for an economist, and this my case. I convert myself to Data Scientist thanks to my econometrics knowledge applied with Anaconda.
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.