We performed a comparison between Datadog and DataRobot based on real PeerSpot user reviews.
Find out in this report how the two AIOps solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."We like the distributed tracing and flame graphs for debugging. This has been invaluable for us during periods of high traffic or red alert conditions."
"The solution has improved the organization by providing good insights into app performance and offering good dashboards."
"The application performance monitoring is pretty good."
"It has provided visibility with ease of implementation and allowed multiple teams to quickly onboard it."
"If we have a large load for users using our basic Datadog, it will immediately fire off an alert notifying us either something's wrong or not."
"We have a better grasp of what is occurring during the deployment cycle. If something fails, we have an idea what has failed, where it has failed, and how it failed to better mitigate the situation."
"We integrate our application logs. It is great to be able to tie our metrics and our traces together."
"It brings in observability, monitoring, and alerting capabilities - all of which we need to operate at scale."
"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."
"DataRobot can be easy to use."
"It's easy to do MLOps operations. It's a lot easier to manage jobs and see the logs if there's any drift in a model."
"The documentation could be improved regarding setting up the agent properly and debugging."
"The pricing is a bit confusing."
"It would be ideal if the product offered a bit more monitoring from our dashboard."
"The menu on the left is pretty dense (and I know it has to be). I never knew about the cmd+k functionality until recently. It would be helpful to offer more tips/cheat sheets to see handy shortcuts like that."
"Alerting timing should be improved to be more fine-tuned and exact."
"The correlation between the logs and the metrics needs improvement as most cases, we might use another logging tool (that is cheaper in cost) which we then have to link together."
"One area where I was really looking for improvement was the CSPM product line. I had really wanted to have team-level visibility for findings, since the team managing the resources has much more context and ability to resolve the issue, as the service owner. However, this has been added to the announcement in a recent keynote."
"We would really like to see more from the Service Catalog."
"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."
"Generative AI has taken pace, and I would like to see how DataRobot assists in doing generative AI and large language models."
"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 20th in AIOps with 3 reviews. Datadog is rated 8.6, while DataRobot is rated 8.6. 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 manage jobs and see the logs if there's any drift in a model, user-friendly, and the data munching is fast". Datadog is most compared with Dynatrace, Azure Monitor, New Relic, AWS X-Ray and Elastic Observability, whereas DataRobot is most compared with Amazon SageMaker, RapidMiner, Microsoft Azure Machine Learning Studio, Alteryx and SAS Predictive Analytics. See our DataRobot vs. Datadog report.
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