

Dynatrace and DataRobot offer distinct solutions for tech buyers. While Dynatrace excels in certain areas, DataRobot stands out for its comprehensive features, which users consider worth the investment.
Features: Dynatrace users appreciate its robust monitoring, automation capabilities, and suitability for enterprise environments. DataRobot users value its machine learning automation, ease of use, and strong analytics. Despite strong features from both, DataRobot’s advanced machine learning automation gives it an edge.
Room for Improvement: Users of Dynatrace suggest enhancements in reporting, usability, and integration capabilities. DataRobot users desire improvements in integration capabilities, the cost-effectiveness of the enterprise version, and better data visualization. Emphasis on better integrations gives DataRobot more to work on compared to Dynatrace’s need for usability tweaks.
Ease of Deployment and Customer Service: User reviews indicate Dynatrace provides a straightforward deployment process with effective customer support. DataRobot offers a smooth deployment experience but has mixed reviews regarding ongoing support quality. Dynatrace’s consistent customer service reputation affords it a slight edge in deployment and support.
Pricing and ROI: Dynatrace incurs higher initial setup costs but is recognized for delivering substantial ROI over time. DataRobot is noted for its valuable ROI, which justifies its cost, but users find the initial pricing steep. Although both promise good ROI, Dynatrace's ease of justifying its cost gives it a pricing advantage.
On average, we're saving about 10 to 15 hours per project.
I have seen a return on investment, specifically with increased data science productivity by four times, time saved with deploying models, and homogeneous analysis models developed easily.
Using Dynatrace directly improved application uptime and reduced customer impacting incidents.
ROI is hard to specify; however, incidents like impending ransomware attacks highlight its value, though those are exceptional events.
Save money by identifying problems, thereby reducing monetary losses on their application side.
They answer all my questions and share guidance on using DataRobot scripts if certain functionalities are not available in the UI.
Being cloud-hosted enables automatic resource scaling, which supports collaboration across teams.
The customer support from DataRobot is proactive and responsive.
They have a good reputation, and the support is commendable.
The technical support from Dynatrace is excellent.
Whenever we faced any issues, we could get timely resolution from their support.
DataRobot's scalability is very strong and grows with my organization's needs.
If it's an enterprise, increasing the number of instances doesn’t pose problems.
It is a powerful tool and helped us to reduce customer downtime and increase work efficiency.
The scalability of Dynatrace is very significant, especially considering the current improvements in their features.
DataRobot is very stable.
Generally, all are stable at ninety-nine point nine nine percent, but if the underlying infrastructure is not deployed correctly, stability may be problematic.
There have been no stability issues with Dynatrace.
Dynatrace is a SaaS product with frequent agent management updates.
DataRobot is a UI-based tool, which means it cannot provide all the features I might manually implement through notebooks or Python.
There is a lack of transparency in the models; sometimes it feels like a black box.
Another improvement that DataRobot needs is integrating the capability to modify the whole pipeline with Python.
The definition of enterprise is loosely used, however, from a holistic security perspective, including infrastructure, network, ports, software, applications, transactions, and databases, there are areas lacking, especially in network monitoring tools.
Dynatrace could enhance cost and licensing structures, as the current pricing can be expensive for large-scale deployments.
I'm specifically looking at AIOps and how we can monitor AIOps-related things, considering we have LLMs and all that stuff.
The setup cost was minimal because it's cloud-hosted, eliminating the need for heavy on-premises infrastructure, allowing us to start using it immediately after purchase.
My experience with pricing, setup cost, and licensing reveals that the price points can be improved and DataRobot is not so cost-effective, especially for smaller organizations.
Dynatrace is known to be costly, which delayed its integration into our system.
If setting up in a large scale environment, it is overwhelming because it is expensive.
The cost can be controlled from our side, and it is very transparent with Dynatrace regarding DPS and licensing.
By automating highly technical aspects like model comparison, DataRobot enhances productivity and reduces project timelines from three months to less than one month.
DataRobot has positively impacted our organization in many ways. First, it has improved efficiency; tasks such as model testing, feature engineering, and predictions that used to take us days or weeks can now be accomplished in hours.
When business leaders ask for the fastest possible solution, DataRobot is our go-to platform.
The integration with Power BI for generating detailed reports is a standout feature.
Dynatrace's AI-driven Davis engine absolutely helps identify performance issues by showing root cause analysis for us up to 200%; whatever is integrated, if it is visible, it can stitch and show.
Dynatrace links compute with services and services with code and other components.
| Product | Mindshare (%) |
|---|---|
| Dynatrace | 15.4% |
| DataRobot | 1.1% |
| Other | 83.5% |


| Company Size | Count |
|---|---|
| Small Business | 2 |
| Midsize Enterprise | 1 |
| Large Enterprise | 5 |
| Company Size | Count |
|---|---|
| Small Business | 78 |
| Midsize Enterprise | 50 |
| Large Enterprise | 299 |
DataRobot captures the knowledge, experience and best practices of the world’s leading data scientists, delivering unmatched levels of automation and ease-of-use for machine learning initiatives. DataRobot enables users to build and deploy highly accurate machine learning models in a fraction of the time.
Dynatrace is an AI-powered software intelligence monitoring platform that accelerates digital transformation and simplifies cloud complexities. Dynatrace is an entirely automated full-stack solution that provides data and answers about the performance of your applications and deep insight into every transaction throughout every application, including the end-user experience. By modernizing and automating enterprise cloud operations, users can deliver an optimal digital experience with higher quality software to customers faster.
Dynatrace offers an all-in-one automated artificial intelligence solution that brings together application performance, cloud and infrastructure, and digital experience monitoring. Dynatrace accelerates performance-driven results through operations, development, and business teams with a shared metrics platform. In addition, users are provided a full-stack monitoring experience with three patented technologies:
What does Dynatrace offer?
Dynatrace redefines how organizations monitor their digital ecosystems. The solution offers:
Reviews from Real Users
Dynatrace is the only solution that provides answers to organizations based on deep insight into each user, transaction, and organization's environment.
Barry P., a managing performance engineer at Medica Health Plans, writes, "With Dynatrace, we have synthetic checks and real-user monitoring of all of our websites, places where members and providers can interact with us over the web. We monitor the response times of those with Dynatrace, and it's all integrated into one place."
A consultant at a tech service company notes, "A feature that's one of the highlights of Dynatrace is the AI. The second most valuable feature is OneAgent. Between infrastructures, applications, operating systems, you can deploy with just a single agent and can practically install and forget about it."
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