Astrato Analytics vs. MATLAB

Astrato Analytics provides a feature-rich application that it easy to use for the non-technical user yet robust enough to create a sophisticated SaaS application. Astrato Analytics provides native integration to all the major large cloud data platforms and the implementation is very straight forward. The value provided through their feature-rich platform and competitive pricing is unmatched.

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.

Incentivized

• Writeback to the database is simple and straightforward and allows us to build apps in the tool with a level of interation that is not possible with other BI tools
• Version control that is built into the workbooks allows us to quickly deploy changes without the fear of losing the older version and maintianing both a historcal updates and the ability to rollback
• Easy connectivity to a wide range of data platforms including Snowflake, Databricks, and Google Workspace within the same tenant allows us to leverage data from each of these platforms for specific use cases

• 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.

Incentivized

• The product is still young, as a consequence, some features aren't as mature as competitors. Astrato has worked to catch up quickly, by rolling out new features regularly
• Better ability to control icons and themes from a central point, instead of having to add/change them on each report

Incentivized

• 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.

Incentivized

It is a very intuitive system, a pleasure to use, practical and simple, for medium to advanced activities. BI supervisors are delighted with much of the functionality, but highlight some weaknesses that they still have, such as the loading speed in HEIC-type files.

Without a doubt, it is a tool that has become essential in our business routine.

Incentivized

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.

Incentivized

Very friendly, with online help, blog and community. The template documentation could be more complete, however.

Incentivized

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.

Incentivized

To scale PowerBi, we would have needed a staff of technical folks and a substantial budget, and we still probably could not have created the robust SaaS application we did with Astrato Analytics. Astrato Analytics allowed for a staff of two to create and rollout a SaaS Application in under 60 days and provided hands on support to us as needed. There really is no comparison.

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.

Incentivized

• The ability to unify multiple platforms in Astrato provides cost savings.

• 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.

Incentivized