AWS DeepComposer vs. Grafana vs. Wolfram Mathematica

Just about any organization with more than one server and more than one cluster as it scales very well. Configuration of the application takes time and finesse to fine tune to where the balance of load time and getting data quickly meets. The plugins add load time but fine tuning for the application to meet demand needs nailed down at implementation

Incentivized

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.

• Alerting through many different medium as Slack, Email, Webhook etc
• Beautiful and unlimited number of dashboards to view your metrics and tweak them as you please
• Log aggregation and powerful Logql to filter and view your logs
• Microservices monitoring
• Large number of plugins and data sources to collect your metrics from almost anywhere

Incentivized

• 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

• There are some settings which we can't configure from UI (Web Console).
• We've open[ed] up configuration files in command line text editors and manually do the settings e.g. LDAP/SSO configuration.
• In terms of visualization, it's best, but it doesn't support log analysis otherwise it could destroy business of all other visualization tools.

• 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 infinitely flexible. If you can imagine it, Grafana can almost certainly do it. Usability may be in the eye of the beholder however, as there is time needed to curate the experience and get the dashboards customized to how it makes sense to you. I know one thing they are working on are more templates, based on data sources

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

Grafana blows Nagios out of the water when it comes to customization. The ability to feed almost any data source makes it very versatile and the cost is great.

Incentivized

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

• Grafana has replaced many higher priced tools
• The integrations are seemless with multiple backends
• Combining graphs and dashboards from multiple data sources is a game changer

Incentivized

• 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