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DataRobot vs Datadog comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Oct 19, 2025

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Datadog
Ranking in AIOps
1st
Average Rating
8.6
Reviews Sentiment
7.0
Number of Reviews
206
Ranking in other categories
Application Performance Monitoring (APM) and Observability (1st), Network Monitoring Software (4th), IT Infrastructure Monitoring (3rd), Log Management (4th), Container Monitoring (2nd), Cloud Monitoring Software (2nd), Cloud Security Posture Management (CSPM) (6th)
DataRobot
Ranking in AIOps
16th
Average Rating
8.6
Reviews Sentiment
7.2
Number of Reviews
5
Ranking in other categories
Predictive Analytics (5th), AI Development Platforms (14th)
 

Mindshare comparison

As of October 2025, in the AIOps category, the mindshare of Datadog is 17.1%, down from 22.6% compared to the previous year. The mindshare of DataRobot is 0.5%, up from 0.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AIOps Market Share Distribution
ProductMarket Share (%)
Datadog17.1%
DataRobot0.5%
Other82.4%
AIOps
 

Featured Reviews

Dhroov Patel - PeerSpot reviewer
Has improved incident response with better root cause visibility and supports flexible on-call scheduling
Datadog needs to introduce more hard limits to cost. If we see a huge log spike, administrators should have more control over what happens to save costs. If a service starts logging extensively, I want the ability to automatically direct that log into the cheapest log bucket. This should be the case with many offerings. If we're seeing too much APM, we need to be aware of it and able to stop it rather than having administrators reach out to specific teams. Datadog has become significantly slower over the last year. They could improve performance at the risk of slowing down feature work. More resources need to go into Fleet Automation because we face many problems with things such as the Ansible role to install Datadog in non-containerized hosts. We mainly want to see performance improvements, less time spent looking at costs, the ability to trust that costs will stay reasonable, and an easier way to manage our agents. It is such a powerful tool with much potential on the horizon, but cost control, performance, and agent management need improvement. The main issues are with the administrative side rather than the actual application.
SagarYadav - PeerSpot reviewer
Automating model comparison speeds up development and reduces timelines
DataRobot is equipped with a GUI-based approach that simplifies the process of feature engineering and model training. It provides AutoML capabilities, which allow for comparing thousands of models and selecting the best-suited one based on business requirements. By automating highly technical aspects like model comparison, DataRobot enhances productivity and reduces project timelines from three months to less than one month.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"The solution's SaaS model is easy to manage and works well in single- or multi-cloud environments."
"The pricing model makes more sense than what we paid for against other competitors."
"Real user monitoring gives us invaluable insights into actual user experiences, helping us prioritize improvements where they matter most."
"Datadog dashboards are pretty great."
"The most valuable features have been: Sharable dashboards, TimeBoards, dogstatsd API, Slack Integration, Event logging API. CloudTrail Events, Tags, alerts, and anomaly detection. EBS Volume Snapshot Age, which they added upon request."
"The integration into AWS is key as well as our software is currently bound to AWS."
"Datadog infrastructure monitoring has helped us identify health issues with our virtual machines, such as high load, CPU, and disk usage, as well as monitoring uptime and alerting when Kubernetes containers have a bad time staying up."
"The ease of correcting these dashboards and widgets when needed is amazing."
"DataRobot is highly automated, allowing data scientists to build models easily."
"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."
"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."
"By automating highly technical aspects like model comparison, DataRobot enhances productivity and reduces project timelines from three months to less than one month."
 

Cons

"Other than being restricted by cost, Datadog's scalability has been a little bit of a challenge to do the initial installation of the agent."
"We have contact with many customers that cover many areas, so we have cases where the infrastructure administration could be improved."
"The query performance could be improved, particularly when handling large datasets, as slower response times can hinder efficiency."
"Lacks some flexibility in the customization."
"It could use some additional features when working with metrics like Grafana or like New Relic has. Datadog does not use library technologies like Dynatrace does. Datadog has machine learning too, but it does not have this option in all layers of monitoring like infrastructure service process in applications."
"I would like better navigability across pages."
"We would like to see smaller or shorter tutorials and video sessions."
"We've had some issues where we had Datadog automatically turned on in AWS regions that we weren't using, which incurred a small but steady cost that amounted to tens of thousands of dollars spent over a few weeks."
"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."
"DataRobot is a UI-based tool, which means it cannot provide all the features I might manually implement through notebooks or Python. In this aspect, I see room for improvement in its functionality."
"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."
"Generative AI has taken pace, and I would like to see how DataRobot assists in doing generative AI and large language models."
"There are some performance issues."
 

Pricing and Cost Advice

"The tool is open-source."
"This solution is budget friendly."
"Licensing is based on the retention period of logs and metrics."
"It didn't scale well from the cost perspective. We had a custom package deal."
"It has always scaled for us. Cost scales up too, but that is not necessarily a bad thing. It's reasonable for what they're providing."
"If you do your homework, you'll find that if you're really concerned with cost, it's good."
"Pricing and licensing are reasonable for what they give you. You get the first five hosts free, which is fun to play around with. Then it's about four dollars a month per host, which is very affordable for what you get out of it. We have a lot of hosts that we put a lot of custom metrics into, and every host gives you an allowance for the number of custom metrics."
"Datadog does not provide any free plans to use the solution. When I start with a proof of concept it would be sensible to have a free plan to test the tool and check whether it fits the requirements of the project. Before the production stage, it is always good to have a free plan with some limited features, number of requests, or logs."
"We dropped the plan to use DataRobot, because we found the pricing to be on the higher sise. We liked DataRobot a lot, but due to the pricing, we dropped that idea."
"The price of DataRobot is good because if you take the price of the solution which is approximately $65,000, it is less than a data scientist. There are very few data scientists available."
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Top Industries

By visitors reading reviews
Financial Services Firm
15%
Computer Software Company
14%
Manufacturing Company
8%
Retailer
6%
Financial Services Firm
14%
Manufacturing Company
11%
Computer Software Company
11%
Retailer
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business80
Midsize Enterprise46
Large Enterprise94
No data available
 

Questions from the Community

Any advice about APM solutions?
There are many factors and we know little about your requirements (size of org, technology stack, management systems, the scope of implementation). Our goal was to consolidate APM and infra monitor...
Datadog vs ELK: which one is good in terms of performance, cost and efficiency?
With Datadog, we have near-live visibility across our entire platform. We have seen APM metrics impacted several times lately using the dashboards we have created with Datadog; they are very good c...
Which would you choose - Datadog or Dynatrace?
Our organization ran comparison tests to determine whether the Datadog or Dynatrace network monitoring software was the better fit for us. We decided to go with Dynatrace. Dynatrace offers network ...
What needs improvement with DataRobot?
DataRobot is a UI-based tool, which means it cannot provide all the features I might manually implement through notebooks or Python. In this aspect, I see room for improvement in its functionality.
What is your primary use case for DataRobot?
In our day-to-day use, I utilize DataRobot to speed up our development process through its GUI capability. Once I set up our connection with a back-end data set, whatever the project I work on next...
What advice do you have for others considering DataRobot?
I would recommend DataRobot because if there is something not included in the UI, I have the freedom to use its Python API, which extends the capability for different use cases. Additionally, I wou...
 

Comparisons

 

Overview

 

Sample Customers

Adobe, Samsung, facebook, HP Cloud Services, Electronic Arts, salesforce, Stanford University, CiTRIX, Chef, zendesk, Hearst Magazines, Spotify, mercardo libre, Slashdot, Ziff Davis, PBS, MLS, The Motley Fool, Politico, Barneby's
Harmoney, Zidisha, ONE Marketing, DonorBureau, Trupanion, Avant
Find out what your peers are saying about DataRobot vs. Datadog and other solutions. Updated: September 2025.
872,706 professionals have used our research since 2012.