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DataRobot vs Datadog comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Oct 1, 2024

Review summaries and opinions

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

Customer Service

Sentiment score
7.6
Datadog's customer service is generally praised for responsiveness and expertise, though some users note delays and lack of phone support.
No sentiment score available
DataRobot's customer service is praised for its responsiveness, knowledge, proactive communication, thorough documentation, and comprehensive assistance.
 

Room For Improvement

Sentiment score
5.6
Datadog users face challenges with billing, integration, interface complexity, and desire more flexibility, support, and improved features.
Sentiment score
5.1
DataRobot needs better customization, deployment flexibility, large dataset handling, performance, and more comprehensive documentation and support resources.
 

Scalability Issues

Sentiment score
7.9
Datadog offers scalable performance and customization but users should monitor rising costs and potential challenges with complex architectures.
Sentiment score
6.3
DataRobot is scalable, integrates easily, automates processes, supports multiple models, and handles large data volumes efficiently.
 

Setup Cost

Sentiment score
6.3
Datadog's pricing varies by organization size, requiring careful monitoring and planning due to complex usage-based billing and potential hidden costs.
No sentiment score available
<p>DataRobot provides scalable, cost-effective AI solutions with flexible pricing tailored to enterprise needs and usage volume.</p>
 

Stability Issues

Sentiment score
8.0
Datadog is praised for its stability and reliable performance, effectively managing disruptions and supporting diverse operational needs.
Sentiment score
8.4
DataRobot is praised for its stability, reliability, seamless integration, efficient error handling, and robust performance even with large datasets.
 

Valuable Features

Sentiment score
8.4
Datadog excels in real-time monitoring, intuitive interface, robust integrations, efficient alerts, and comprehensive performance tracking and system reliability.
Sentiment score
8.5
DataRobot simplifies feature engineering, automates model building, and offers comprehensive MLOps with job management, model drift inspection, and retraining.
 

Categories and Ranking

Datadog
Ranking in AIOps
1st
Average Rating
8.6
Reviews Sentiment
7.4
Number of Reviews
187
Ranking in other categories
Application Performance Monitoring (APM) and Observability (1st), Network Monitoring Software (2nd), 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
7.6
Number of Reviews
4
Ranking in other categories
Predictive Analytics (5th), AI Development Platforms (12th)
 

Mindshare comparison

As of November 2024, in the AIOps category, the mindshare of Datadog is 24.1%, down from 27.1% 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.
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816,406 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Educational Organization
37%
Computer Software Company
11%
Financial Services Firm
10%
Manufacturing Company
7%
Educational Organization
25%
Financial Services Firm
11%
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...
 

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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: October 2024.
816,406 professionals have used our research since 2012.