We performed a comparison between Datadog and DataRobot based on real PeerSpot user reviews.
Find out what your peers are saying about Datadog, Dynatrace, New Relic and others in AIOps."Flame graphs are pretty useful for understanding how GraphQL resolves our federated queries when it comes to identifying slow points in our requests. In our microservice environment with 170 services."
"The integration into AWS is key as well as our software is currently bound to AWS."
"It has enhanced the performance of my team."
"Straightforward to integrate and automate."
"We can handle debugging and find out why things are breaking in our applications."
"The solution is useful for monitoring logs."
"Dashboards and their versatility are among the most valuable features."
"I have found error reporting and log centralization the most valuable features. Overall, Datadog provides a full package solution."
"DataRobot can be easy to use."
"We especially like the initial part of feature engineering, because feature engineering is included in most engines, but DataRobot has an excellent way of picking up the right features."
"While I like the ease of use, when compared with Tenable Nessus they could still improve their usability."
"I would like the tooling to have better integration in Slack, specifically sending out reminders to the relevant people to take breaks, do a retrospective, and specify with emojis which messages to log."
"Datadog could make their use cases more visible either through their docs or tutorial videos."
"The dashboard could be improved. It would be helpful to get a view of specific things that we need to monitor for our application."
"Billing should be more transparent."
"I've only been using Datadog for a few months, and at first, it was frankly overwhelming in terms of both the UI and the available capabilities."
"We need more integration functionality, including certain metrics integration."
"We have contact with many customers that cover many areas, so we have cases where the infrastructure administration could be improved."
"The business departments will love to work with DataRobot because they use the tool to investigate their data, such as targeting what they want to investigate. They don't need any data scientists near them. They can investigate at eye level and bring into the BI tool, or can bring it to the data scientist. Data scientists can use this tool to bring increase the solution to the maximum. All the others can use it, but not to the maximum."
"If we could include our existing Python or R code in DataRobot, we could make it even better. The DataRobot that we have is specific to an industry, but most of the time we would have our own algorithms, which are specific to our own use case. If we had a way by which we could integrate our proprietary things into DataRobot with a simple integration, it would help us a lot."
Earn 20 points
Datadog is ranked 1st in AIOps with 137 reviews while DataRobot is ranked 19th in AIOps. Datadog is rated 8.6, while DataRobot is rated 8.0. The top reviewer of Datadog writes "Very good RUM, synthetics, and infrastructure host maps". On the other hand, the top reviewer of DataRobot writes "Easy to use, priced well, and can be customized". Datadog is most compared with Dynatrace, Azure Monitor, New Relic, AWS X-Ray and AppDynamics, whereas DataRobot is most compared with Amazon SageMaker, RapidMiner, Microsoft Azure Machine Learning Studio, SAS Predictive Analytics and Alteryx.
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