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DataRobot vs Datadog comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Oct 1, 2024
 

Categories and Ranking

Datadog
Ranking in AIOps
1st
Average Rating
8.6
Reviews Sentiment
7.1
Number of Reviews
187
Ranking in other categories
Application Performance Monitoring (APM) and Observability (1st), Network Monitoring Software (3rd), IT Infrastructure Monitoring (2nd), Log Management (3rd), Container Monitoring (1st), Cloud Monitoring Software (1st), Cloud Security Posture Management (CSPM) (6th)
DataRobot
Ranking in AIOps
17th
Average Rating
8.6
Reviews Sentiment
7.1
Number of Reviews
4
Ranking in other categories
Predictive Analytics (5th), AI Development Platforms (12th)
 

Mindshare comparison

As of December 2024, in the AIOps category, the mindshare of Datadog is 22.8%, down from 26.2% compared to the previous year. The mindshare of DataRobot is 0.5%, up from 0.1% 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.
Raviteja Guna - PeerSpot reviewer
Highly automated solution allowing data scientists to build models easily
Based on your similar requirements, V10.0 has very cool features related to AI Generation. I would suggest the team, too. This is very good for data scientists or people who don't want to code. Even the documentation is well-maintained in terms of its capabilities. It's easy to navigate. The support documents are good. Even someone with basic IT knowledge can easily navigate. If you're an IT engineer, you can efficiently perform operations using it. We have deployed eight to nine use cases on DataRobot and have seen a tremendous response in accuracy and performance. We are pleased because we conducted a comparison. We took a model we built using a sample Python on a local machine and applied the same data and process using DataRobot Autopilot. The results were pretty amazing, with promising accuracy and recall. The accessibility is so easy. Even a college graduate with essential experience can use it. Suppose I do the same model in Databricks and want to monitor my MLOps pipeline. So, I need to use a third-party framework again, like MLflow, Kubeflow, Airflow, or whatever. I need to build my dashboards and everything, customization dashboards. However, everything is available in DataRobot. I can use it directly. They have a new option called DataRobot apps. So, on the predictions, we can even create customized apps. I can build my dashboard, and I can develop my applications. Overall, I rate the solution an eight out of ten.

Quotes from Members

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

Pros

"Real user monitoring has made triaging any possible bugs our users might face a lot easier."
"The application performance monitoring is pretty good."
"Our primary alerts, based on metrics and synthetic transactions, are the most used and relied upon for decreased MTTA/MTTR across all of our platforms. This is followed by deep log analysis that enables us to quickly and easily get to a preliminary root cause that someone on the infrastructure, platform or development teams can take and focus their attention on the precise target that Datadog revealed as the issue to be remediated."
"The installation step is pretty straightforward."
"The feature I have found most valuable is when I can reuse existing monitors and alerts for new dashboards."
"The seamless integration between Datadog and hundreds of apps makes onboarding new products and teams a breeze."
"It has enhanced the performance of my team."
"The most valuable feature is the dashboards that are provided out of the box, as well as ones we were able to configure."
"DataRobot is highly automated, allowing data scientists to build models easily."
"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."
 

Cons

"Delta traces on the Golang profiler are extremely expensive concerning memory utilization."
"They need to offer better/more customization on what logs we get and making tracing possible on Edge runtime logs is a real requirement."
"More helpful log search keywords/tips would be helpful in improving Datadog's log dashboard."
"Datadog is expensive."
"The more tools that they can build that allow you to run AWX playbooks, or other similar fixes, would benefit clients greatly."
"The ability to find what you are looking for when starting out could be improved."
"As a new customer, the Datadog user interface is a bit daunting."
"There could be more easily identifiable documentation on how to find different things on the platform."
"Generative AI has taken pace, and I would like to see how DataRobot assists in doing generative AI and large language models."
"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."
"There are some performance issues."
 

Pricing and Cost Advice

"Pricing seemed easy until the bill came in and some things were not accounted for."
"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."
"Pricing is somewhat affordable compared to other solutions but in order to really lower the costs of other products you need to plan very carefully your resources usage, otherwise, it can get expensive real quick."
"It costs the same amount it would if we were hosting it ourselves, so we are incredibly happy with the cost."
"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."
"The solution's pricing depends on project volume."
"While it is an expensive product, I would rate the pricing level at four out of five."
"This solution is budget friendly."
"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
Educational Organization
38%
Computer Software Company
10%
Financial Services Firm
10%
Manufacturing Company
5%
Educational Organization
25%
Financial Services Firm
12%
Computer Software Company
9%
Manufacturing Company
7%
 

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?
There are some performance issues when it comes to improvements. They also offer storage-related services compared to other tools like Admin, Azure, or AWS. It is easy to plug and play. Third-party...
What is your primary use case for DataRobot?
We work on AI and ML use cases related to technology and IT.
What advice do you have for others considering DataRobot?
Based on your similar requirements, V10.0 has very cool features related to AI Generation. I would suggest the team, too. This is very good for data scientists or people who don't want to code. Eve...
 

Comparisons

 

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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: December 2024.
824,053 professionals have used our research since 2012.