Likelihood to Recommend Kibana integrates seamlessly with Elastic Search which gives us access to parse and analyze data generated from our systems in order to make decisions. Also, Kibana helps us create insightful reports and dashboards that give us insights into the end-users usage on the system and helps us find the root cause of issues as well.
Read full review 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.
Steffen Jäschke Projektspezialist bei Steffen Jäschke EinzUnt Physik, Berechnungen
Read full review Pros Fast searches with powerful index. Beautiful data visualizations. Real-time observability. Read full review 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. Read full review Cons Some performance issues with large datasets. Linking to dashboards makes extremely long urls. Lack of reports. Read full review 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. Read full review Support Rating We did not use the official Kibana support. Documentation was easy enough to follow.
Read full review 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.
Read full review Alternatives Considered Kibana has a better usability experience, the core features I was using existed in all of them. I liked more in Kibana how you can easily create dashboards, charts, and reports without the need to be a tech person.
Read full review 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.
Read full review Return on Investment Issues that affect checkout experiences for customers are able to be prioritized and solved quickly. We are able to more efficiently use resources due to the automation of reporting alerts. Decreasing employee resources needed. Visualization allows us to quickly share issues and explain to coworkers in order to escalate issues that can cost our bottom line. Read full review 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 Read full review ScreenShots