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DataRobot vs Devo comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Sep 16, 2024

Review summaries and opinions

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

ROI

Sentiment score
9.0
DataRobot enhanced prediction accuracy, reduced analysis time, simplified processes, and improved efficiency, leading to better decisions and cost savings.
Sentiment score
7.7
Devo enhances root cause remediation by 50%, offering cost savings, scalability, fast cloud deployment, and diverse client flexibility.
On average, we're saving about 10 to 15 hours per project.
Senior Data Reporting Analyst at a educational organization with 1,001-5,000 employees
 

Customer Service

Sentiment score
7.5
DataRobot excels in customer service and scalability, but could improve response speed and documentation for large datasets.
Sentiment score
7.0
Devo's customer service is responsive and efficient, but improvements are needed in documentation and onboarding support.
They answer all my questions and share guidance on using DataRobot scripts if certain functionalities are not available in the UI.
Staff Specialist Data Scientist at a tech vendor with 5,001-10,000 employees
Being cloud-hosted enables automatic resource scaling, which supports collaboration across teams.
Senior Data Reporting Analyst at a educational organization with 1,001-5,000 employees
 

Scalability Issues

Sentiment score
4.6
DataRobot is scalable, integrates easily, automates processes, supports multiple models, and handles large data volumes efficiently.
Sentiment score
7.6
Devo's cloud-based structure ensures seamless scalability, supporting diverse roles and extensive deployments for effective data handling and monitoring.
 

Stability Issues

Sentiment score
7.7
DataRobot is praised for stability and reliability, with enhancements improving user satisfaction across diverse analytics scenarios.
Sentiment score
7.3
Devo is highly stable and reliable, with minimal issues and efficient management, evolving positively as a cloud-native service.
 

Room For Improvement

DataRobot faces customization, integration, and performance challenges; improved AI support, transparency, and community engagement are needed.
Devo faces performance, customization, integration, and pricing challenges, needing improvements in AI, reporting, and dashboard capabilities.
DataRobot is a UI-based tool, which means it cannot provide all the features I might manually implement through notebooks or Python.
Staff Specialist Data Scientist at a tech vendor with 5,001-10,000 employees
There is a lack of transparency in the models; sometimes it feels like a black box.
Senior Data Reporting Analyst at a educational organization with 1,001-5,000 employees
Integrations with other sandboxes could be improved to better interpret data using AI and machine learning models.
Strategic Account Executive at a computer software company with 51-200 employees
 

Setup Cost

<p>DataRobot provides scalable, cost-effective AI solutions with flexible pricing tailored to enterprise needs and usage volume.</p>
Devo offers competitive pricing with flexible licensing, though metadata costs and subscription models may affect overall expenses.
The setup cost was minimal because it's cloud-hosted, eliminating the need for heavy on-premises infrastructure, allowing us to start using it immediately after purchase.
Senior Data Reporting Analyst at a educational organization with 1,001-5,000 employees
 

Valuable Features

DataRobot automates feature engineering and model testing, enhancing productivity and decision-making with user-friendly, scalable integration.
Devo's Activeboards offer intuitive, fast data visualization with high-speed queries, real-time analytics, and seamless integration for effective insights.
DataRobot has positively impacted our organization in many ways. First, it has improved efficiency; tasks such as model testing, feature engineering, and predictions that used to take us days or weeks can now be accomplished in hours.
Senior Data Reporting Analyst at a educational organization with 1,001-5,000 employees
By automating highly technical aspects like model comparison, DataRobot enhances productivity and reduces project timelines from three months to less than one month.
Staff Specialist Data Scientist at a tech vendor with 5,001-10,000 employees
When they see a spike in a line chart for a failed login, which could be a true or false attempt, they can click that spike, and a table widget on the same active board instantly populates with raw logs of data for those specific failed logins.
Strategic Account Executive at a computer software company with 51-200 employees
 

Categories and Ranking

DataRobot
Ranking in AIOps
15th
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
6
Ranking in other categories
Predictive Analytics (5th), AI Development Platforms (15th), AI Observability (66th), AI Finance & Accounting (4th)
Devo
Ranking in AIOps
20th
Average Rating
8.4
Reviews Sentiment
6.8
Number of Reviews
23
Ranking in other categories
Log Management (28th), Security Information and Event Management (SIEM) (24th), IT Operations Analytics (11th)
 

Mindshare comparison

As of January 2026, in the AIOps category, the mindshare of DataRobot is 1.0%, up from 0.5% compared to the previous year. The mindshare of Devo is 1.1%, up from 0.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AIOps Market Share Distribution
ProductMarket Share (%)
DataRobot1.0%
Devo1.1%
Other97.9%
AIOps
 

Featured Reviews

Naqash Ahmed - PeerSpot reviewer
Senior Data Reporting Analyst at a educational organization with 1,001-5,000 employees
Automation has improved efficiency and decision-making while big data handling and transparency still need work
Aside from the many advantages of DataRobot, I believe there are areas that could be improved based on my experience. There is a lack of transparency in the models; sometimes it feels like a black box. For example, when I uploaded a large data set of about two gigabytes for processing, the time taken was slower than expected. Additionally, the handling of bigger data sets could be better, as it performs extremely well with smaller datasets but can lag with larger ones. The integration with some other tools used in our organization can also be challenging, and more flexibility for custom pre-processing and advanced model tuning would be beneficial. In terms of support and documentation, I believe improvements are needed. For instance, the response time from DataRobot could be quicker, which would be appreciated when we need assistance. The documentation is generally sufficient, but it can be lengthy and could use more real-world examples and step-by-step tutorials for better clarity. Lastly, creating a client community where users can share experiences and solutions might enhance the overall value and learning curve.
FR
Strategic Account Executive at a computer software company with 51-200 employees
Has improved investigative workflows with interactive dashboards and simplified data correlation
The data analytics cloud component focuses on real-time analytics, which is very impressive. The SIEM collects and correlates logs data from different sources and can integrate with ServiceNow, hardware asset management, and software asset management. The security orchestration, automation, and response (SOAR) is another valuable feature. The security data platform serves as the foundation of Devo. Regarding advanced query capabilities, Devo offers several models including query logs, visual query builder, language integrated query, and SQL, with SQL being the most frequently used querying data capability. The single pane of glass that Devo offers is the SOC. The tools in Devo's active ports are for investigating, not just viewing data. They are more interactive than other market solutions. The drill-down reports capabilities allow analysts to click on any element in a widget. When they see a spike in a line chart for a failed login, which could be a true or false attempt, they can click that spike, and a table widget on the same active board instantly populates with raw logs of data for those specific failed logins. This is particularly important for enterprise companies with numerous endpoints and users. The dynamic filtering of inputs significantly reduces the time cybersecurity analysts spend trying to figure out failed logins and identifying false positives.
report
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Manufacturing Company
12%
Computer Software Company
10%
Retailer
8%
Financial Services Firm
16%
University
9%
Computer Software Company
9%
Manufacturing Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business8
Midsize Enterprise4
Large Enterprise11
 

Questions from the Community

What is your experience regarding pricing and costs for DataRobot?
While pricing falls more under my IT colleagues, from my perspective, the overall experience feels justified. The premium pricing is reasonable for the value provided, and I'd say it's worth the in...
What needs improvement with DataRobot?
Aside from the many advantages of DataRobot, I believe there are areas that could be improved based on my experience. There is a lack of transparency in the models; sometimes it feels like a black ...
What is your primary use case for DataRobot?
My main use case for DataRobot is to perform predictive analysis and automation of machine learning workflows. I use it to quickly build, test, and deploy models without extensive coding. One of th...
What is your experience regarding pricing and costs for Devo?
Compared to Splunk or SentinelOne, it is really expensive. I rate the product’s pricing a nine out of ten, where one is cheap and ten is expensive.
What needs improvement with Devo?
The single pane of glass that Devo offers could be improved. The tools in Devo's active ports need enhancement in their investigative capabilities. The drill-down reports capabilities, while useful...
What is your primary use case for Devo?
During my time at MetaBase Q and as a partner integrator of ServiceNow, I had the chance to understand and be part of projects integrating SOCs, NOCs, and Security Operation Centers with Devo. Most...
 

Comparisons

 

Overview

 

Sample Customers

Harmoney, Zidisha, ONE Marketing, DonorBureau, Trupanion, Avant
United States Air Force, Rubrik, SentinelOne, Critical Start, NHL, Panda Security, Telefonica, CaixaBank, OpenText, IGT, OneMain Financial, SurveyMonkey, FanDuel, H&R Block, Ulta Beauty, Manulife, Moneylion, Chime Bank, Magna International, American Express Global Business Travel
Find out what your peers are saying about DataRobot vs. Devo and other solutions. Updated: December 2025.
881,114 professionals have used our research since 2012.