Kibana vs. Wolfram Mathematica

Great for teams big and small that want a single pane of glass for understanding their systems, from dev, to staging, to production. Well-suited for teams that need to preserve logs for long-term compliance reasons, and also mine their logs for useful operational insights. Highly recommended as both an open source project and a commercial offering with fantastic paid support.

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.

• searching
• near real-time

Incentivized

• Doing the analysis is very good, plotting the data, getting the insight from data using this is easy and output looks pretty good
• Solving mathematical problems, with detailed solutions step by step (mainly calculus problems)
• You can also query this knowledge engine in simple English. It has ability to interpret that and will give you answer accordingly
• Nowadays, it provides API to use, so you can do image processing, video/audio using this

Incentivized

• Improved tutorial/ user guidance
• Improved labeling for sources
• Ease of login and sharing with coworkers

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.

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Its usability is generally good and it provides teams with a basic to intermediate understanding about data visualization. It is very user-friendly when it comes to creating dashboards. The UI is very good and simple. Its integration with other tools for alerting and reporting is amazing. But its advance features have a learning curve and a first timer needs some time to use the advance features.

Incentivized

I have not contacted Kibana support.

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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

Well when it comes to using Kibana when compared to Datadog, I can say that Kibana is pretty [...] cheap. Apart from APM and Datadog hosted agents, Kibana gives a good competition to Datadog for real time log analysis as well as metrics analysis. While OpsGenie is a great tool for alerting, it lacks visualization when compared to Kibana. Grafana is another opensource tool that gives a lot of insights like Kibana but Grafana cannot be easily integrated with OpenSearch.

Incentivized

The ability to manipulate algebraic expressions, nested lists, and data structures in Mathematica was unequalled when I first did the comparison. Since then, I've stuck with Mathematica mostly because it's "the tool I know."

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• First stop when diagnosing production performance issues.

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• Mathematica is our "go to" environment for developing solutions for our clients, so I suppose you could say that it is solely responsible for our revenues. On occasion we do use other platforms but Mathematica is a core component of our offer to clients.

Incentivized