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DataRobot vs Datadog comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jan 5, 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
7.1
Number of Reviews
188
Ranking in other categories
Application Performance Monitoring (APM) and Observability (1st), Network Monitoring Software (3rd), IT Infrastructure Monitoring (2nd), Log Management (3rd), Container Monitoring (2nd), Cloud Monitoring Software (1st), Cloud Security Posture Management (CSPM) (7th)
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 (13th)
 

Mindshare comparison

As of March 2025, in the AIOps category, the mindshare of Datadog is 20.9%, down from 25.8% compared to the previous year. The mindshare of DataRobot is 0.6%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AIOps
 

Featured Reviews

Kevin Palmer - PeerSpot reviewer
Useful log aggregation and management with helpful metrics aggregation
Datadog provides us value in three major ways: First, Datadog provides best-in-class functionality in many, if not all, of the products to which we subscribe (infrastructure, APM, log management, serverless, synthetics, real user monitoring, DB monitoring). In my experience with other tools that provide similar functionality, Datadog provides the largest feature set with the most flexibility and the best performance. Second, Datadog allows us to access all of those services in one place. Having to learn and manage only one tool for all of those purposes is a major benefit. Third, Datadog provides significant connectivity between those services so that we can view, summarize, organize, translate and correlate our data with maximum effect. Not needing to manually integrate them to draw lines between those pieces of information is a huge time savings for us.
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

"Profiling has been made easier."
"Real user monitoring gives us invaluable insights into actual user experiences, helping us prioritize improvements where they matter most."
"The most valuable feature is the dashboards that are provided out of the box, as well as ones we were able to configure."
"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 most useful feature is the APM."
"The infrastructure monitoring capabilities, especially for our Kubernetes clusters, have helped us optimize resource allocation and reduce costs."
"Datadog is easy to use and easy to deploy. It's a better solution compared to others on the market in terms of being budget friendly for our customers."
"The selection of monitors is a big feature I have been working with."
"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."
"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 is highly automated, allowing data scientists to build models easily."
"DataRobot can be easy to use."
 

Cons

"I want to applaud the efforts in making the UI extremely usable and approachable. My suggestion would be to take another look at how the menu structure is put together, however. Even after using the platform mostly every day for months, I still find myself trying to find a service or feature in the menus."
"Datadog could always lower the price!"
"I'm not sure if Datadog can monitor K8s deployments in real-time. For instance, being able to see a deployment step by step visually. This would be helpful if there were any incidents during the deployment."
"The documentation leaves a lot to be desired for new users."
"The monitors need improvement."
"The product is quite complex, and there are so many features that I either didn't know about or wasn't sure how to use."
"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."
"Datadog is too pricey when compared to its competitors, and this is something that its always on my mind during the decision-making process."
"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."
"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."
 

Pricing and Cost Advice

"Pricing seemed easy until the bill came in and some things were not accounted for."
"The solution's pricing depends on project volume."
"Licensing is based on the retention period of logs and metrics."
"Sometimes it's very hard to project how much it will cost for the monthly subscription for the next month when you add certain features. Having better visibility of the cost would give a better experience."
"It is easy to run up a large bill, so become familiar with the cost of each piece of your bill and use the metrics they supply to estimate and monitor your bill."
"The solution is fairly priced but history and log storage can get costly depending on your needs."
"If you do your homework, you'll find that if you're really concerned with cost, it's good."
"I am not satisfied with its licensing. Its payment is based on the exported data, and there was an explosion of the data for three or four weeks. My customer was not alerted, and there was no way for them to see that there has been an explosion of data. They got a big invoice for one or two months. The pricing model of Datadog is based on the data. The customer was quite surprised about not being alerted about this explosion of data. They should provide some kind of alert when there is an increase in usage."
"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."
"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."
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Top Industries

By visitors reading reviews
Educational Organization
37%
Computer Software Company
10%
Financial Services Firm
10%
Manufacturing Company
5%
Educational Organization
21%
Financial Services Firm
13%
Manufacturing Company
8%
Computer Software Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
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: March 2025.
842,296 professionals have used our research since 2012.