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."I find the greatest feature is being able to search across logs from various microservices."
"This spectrum of solutions has allowed us to track down bugs faster and more rapidly, which allows us to limit revenue lost during downtime."
"Datadog dashboards are pretty great."
"I like the amount of tooling and the number of solutions they sold with their monitoring. Datadog was highly intuitive to use."
"It has a nice UI."
"Datadog's ability to group and visualize the servers and the data makes it relatively easy for the root cause analysis."
"The observability on offer is the most useful aspect of the product."
"It has saved us a lot of trouble in implementation."
"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."
"I think better access to their engineers when we have a problem could be better."
"There is always room for improvement when dealing with cloud-based technologies. Mainly, I would say, it's just increasing our offerings to attract various other types of industries and businesses across more fields."
"The FinOps needs improvement."
"Ingesting data from various sources to monitor the log metrics of the system can always improve so that, if something goes wrong, the right teams are alerted."
"Once Datadog has gained wide adoption, it can often be overwhelming to both know and understand where to go to find answers to questions."
"The ease of implementation needs improvement."
"Datadog could be improved if it could detect other software in a container or server."
"Datadog lacks a deeper application-level insight. Their competitors had eclipsed them in offering ET functionality that was important to us. That's why we stopped using it and switched to New Relic. Datadog's price is also high."
"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 20th 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 Elastic Observability, whereas DataRobot is most compared with Amazon SageMaker, RapidMiner, Microsoft Azure Machine Learning Studio, Alteryx and SAS Predictive Analytics.
See our list of best AIOps vendors.
We monitor all AIOps reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.