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."It has provided visibility with ease of implementation and allowed multiple teams to quickly onboard it."
"The observability pipelines are the most valuable aspect of the solution."
"It has a high-level insight into the infrastructure model of the application and provides important detailed data on the host and metrics, which is the main concern of our customers."
"Even if we don't end up using Datadog, it revealed problems and optimizations to us that weren't obvious before."
"APM is great and has provided low-effort out-of-the-box observability for various services."
"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 infrastructure monitoring capabilities are really valuable. You can just log on and see everything that is happening within an IT environment."
"Datadog is providing efficiency in the products we develop for the wireless device engineering department."
"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."
"Deploying the agents is still very manual."
"I would love to see more metrics or analytics in IoT devices."
"The sheer amount of products that are included can be overwhelming."
"Datadog could have a better business analysis module."
"In the past two years, there have been a couple of outages."
"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."
"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."
"If there were a more cost-effective manner of deploying the tool, we'd be more likely to adopt it more widely."
"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.
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