Dynatrace is an APM scaled for enterprises with cloud, on-premise, and hybrid application and SaaS monitoring. Dynatrace uses AI-supported algorithms to provide continual APM self-learning and predictive alerts for proactive issue resolution.
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Tableau Desktop
Score 8.3 out of 10
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Tableau Desktop is a data visualization product from Tableau. It connects to a variety of data sources for combining disparate data sources without coding. It provides tools for discovering patterns and insights, data calculations, forecasts, and statistical summaries and visual storytelling.
Dynatrace is well suited to a number of tasks. It is important to determine who the end users are and gather good information to tailor their experience accordingly. For instance, business/marketing should not have access to some of the more technical data, and business metrics can be a distraction for IT operations personnel.
Tableau Desktop is one the finest tool available in the market with such a wide range of capabilities in its suite that makes it easy to generate insights. Further, if optimally designed, then its reports are fairly simple to understand, yet capable enough to make changes at the required levels. One can create a variety of visualizations as required by the business or the clients. The data pipelines in the backend are very robust. The tableau desktop also provides options to develop the reports in developer mode, which is one of the finest features to embed and execute even the most complex possible logic. It's easier to operate, simple to navigate, and fluent to understand by the users.
We loved Dynatrace's ability to show the data flow - from the front end points through the back end points straight to the database and various API's. It was advanced in its data visualization. This is useful for debugging - showing when/where the errors are. It can even enable non-technical individuals in the corporation to help debug
Dynatrace has some great highly customizable integration options as well as monitoring. You can configure your layout & integration options to create custom monitoring alerts for your applications performance. Further you can increase the extensibility of using a REST API on your architecture.
Some advanced dev-ops systems are utilizing Kubernetes/docker aswell as Node.JS - Dynatrace was able to log and help understand all of our dev-ops needs. It gave us native alerts based off of deviations from the baseline that we set during initial configuration. These metrics are priceless.
An excellent tool for data visualization, it presents information in an appealing visual format—an exceptional platform for storing and analyzing data in any size organization.
Through interactive parameters, it enables real-time interaction with the user and is easy to learn and get support from the community.
Dynatrace does not monitor easily on a C-based application.
The way DPGR is addressed by Dynatrace is not very complete, and not clear. One thing is to mask the IP and request attributes but is not enough, the replay session feature is great but raises serious questions about user tracking.
We have already renewed our purchase with the company. They make it easy for us to get a temporary license for our contingency site that is only used for testing twice a year. We are expanding our license with for this tool. We find it very useful and will renew it again.
Our use of Tableau Desktop is still fairly low, and will continue over time. The only real concern is around cost of the licenses, and I have mentioned this to Tableau and fully expect the development of more sensible models for our industry. This will remove any impediment to expansion of our use.
I really liked how easy it was to deploy the SaaS vesion of Dynatrace in our environment. We have a lot of tools that have plenty of capability but they don't get a whole lot of use because they would require someone who is an expert to use them. With the SaaS version of Dynatrace, all the admin functions are taken care of by the Dynatrace team (updates, patches, new features, bugs, etc.) and our small shop can focus on getting valuable metrics, alerts and issue resolution from the product.
Tableau Desktop has proven to be a lifesaver in many situations. Once we've completed the initial setup, it's simple to use. It has all of the features we need to quickly and efficiently synthesize our data. Tableau Desktop has advanced capabilities to improve our company's data structure and enable self-service for our employees.
When used as a stand-alone tool, Tableau Desktop has unlimited uptime, which is always nice. When used in conjunction with Tableau Server, this tool has as much uptime as your server admins are willing to give it. All in all, I've never had an issue with Tableau's availability.
Tableau Desktop's performance is solid. You can really dig into a large dataset in the form of a spreadsheet, and it exhibits similarly good performance when accessing a moderately sized Oracle database. I noticed that with Tableau Desktop 9.3, the performance using a spreadsheet started to slow around 75K rows by about 60 columns. This was easily remedied by creating an extract and pushing it to Tableau Server, where performance went to lightning fast
Given that Dynatrace has become an informal industry standard, the plethora of information available on forums is massive. Most problems or roadblocks you come across are most likely (almost certainly, in fact) already solved and solutions available on these forums. The tech support at Dynatrace is also quite good, with prompt and knowledgeable people at their end.
I have never really used support much, to be honest. I think the support is not as user-friendly to search and use it. I did have an encounter with them once and it required a bit of going back and forth for licensing before reaching a resolution. They did solve my issue though
It is admittedly hard to train a group of people with disparate levels of ability coming in, but the software is so easy to use that this is not a huge problem; anyone who can follow simple instructions can catch up pretty quickly.
The training for new users are quite good because it covers topic wise training and the best part was that it also had video tutorials which are very helpful
Again, training is the key and the company provides a lot of example videos that will help users discover use cases that will greatly assist their creation of original visualizations. As with any new software tool, productivity will decline for a period. In the case of Tableau, the decline period is short and the later gains are well worth it.
Synthetic Monitoring automatically does what other products do only through the use of other tools or through the development of user applications that still have a high cost of maintenance. The other products are not immediately usable and require many customizations. Through the use of configuration automatisms, you can be immediately operational and, in our case, we detected several imperfections in the applications.
If we do not have legacy tools which have already been set up, I would switch the visualization method to open source software via PyCharm, Atom, and Visual Studio IDE. These IDEs cannot directly help you to visualize the data but you can use many python packages to do so through these IDEs.
Tableau Desktop's scaleability is really limited to the scale of your back-end data systems. If you want to pull down an extract and work quickly in-memory, in my application it scaled to a few tens of millions of rows using the in-memory engine. But it's really only limited by your back-end data store if you have or are willing to invest in an optimized SQL store or purpose-built query engine like Veritca or Netezza or something similar.
Tableau was acquired years ago, and has provided good value with the content created.
Ongoing maintenance costs for the platform, both to maintain desktop and server licensing has made the continuing value questionable when compared to other offerings in the marketplace.
Users have largely been satisfied with the content, but not with the overall performance. This is due to a combination of factors including the performance of the Tableau engines as well as development deficiencies.
