Astrato Analytics vs. Wolfram Mathematica

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.

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.

• 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 allows straightforward integration of analytic analysis of algebraic expressions and their numerical implemented.
• Supports varying programmatic paradigms, so one can choose what best fits the problem or task: pure functions, procedural programming, list processing, and even (with a bit of setup) object-oriented programming.
• The extensive and rich tools for graphical rendering make it very easy to not just get 2D and 3D renderings of final output, but also to do quick-and-dirty 2D and 3D rendering of intermediate results and/or debugging results.

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

• 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.

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

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

Incentivized

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.

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.

We have evaluated and are using in some cases the Python language in concert with the Jupyter notebook interface. For UI, we using libraries like React to create visually stunning visualizations of such models. Mathematica compares favorably to this alternative in terms of speed of development. Mathematica compares unfavorably to this alternative in terms of license costs.

Incentivized

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

• Easy to solve huge mathematical equations, so it saved time there
• Doing analysis and plotting graphs is also another plus point
• Learning is very slow, and it took lot of time to learn its scripting language

Incentivized