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DataRobot vs Moogsoft comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jul 13, 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

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)
Moogsoft
Ranking in AIOps
9th
Average Rating
7.8
Reviews Sentiment
6.1
Number of Reviews
16
Ranking in other categories
IT Infrastructure Monitoring (21st), IT Operations Analytics (5th)
 

Mindshare comparison

As of October 2025, in the AIOps category, the mindshare of DataRobot is 0.5%, up from 0.5% compared to the previous year. The mindshare of Moogsoft is 3.3%, up from 3.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AIOps Market Share Distribution
ProductMarket Share (%)
Moogsoft3.3%
DataRobot0.5%
Other96.2%
AIOps
 

Featured Reviews

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.
Siddharth_Jain - PeerSpot reviewer
Filters the noise and consolidating alerts into a single situation report
Moogsoft's integration options are somewhat limited. It primarily relies on webhooks and APIs for data input, meaning external systems must push data to Moogsoft; it cannot pull data independently. If I want to connect CloudWatch or Prometheus to Moogsoft, I have to write custom code on the Prometheus side to send data through Moogsoft’s APIs or webhooks. Other monitoring tools like Splunk and Dynatrace typically have agents that reside on the system, automatically collecting and sending data. This difference can create challenges for teams needing seamless integration. Although Moogsoft has developed some plugins, such as those for Grafana and Zabbix, that are ready to use, they don’t have comprehensive support for every tool. Splunk has developed an AI assistant that can answer your queries and everything else. Moogsoft lacks that. Dynatrace has this AI component that will identify things on its own. On the other end, Moogsoft, you must set up the workflow. You have to come and set up the cookbooks. ServiceNow also has good event correlation. Splunk is fantastic with the event correlation.

Quotes from Members

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

Pros

"By automating highly technical aspects like model comparison, DataRobot enhances productivity and reduces project timelines from three months to less than one month."
"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."
"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."
"DataRobot can be easy to use."
"The tool's event correlation and AI are its strongest parts."
"Moogsoft helps manage alert fatigue by consolidating various alerts into a single portal instead of monitoring them across different devices, allowing team members to own alerts and monitor them efficiently, which benefits the whole team."
"There are AI features in Moogsoft. Moogsoft has one wonderful feature that allows you to convert multiple alarms into situations. Generally, all other MoM tools get the alarms, and then convert it into an incident directly. There is one extra layer they have added before converting any alarm into an incident. Suppose there are multiple alarms that are somehow all related to a single source of issue. It converts all the alarms into a single situation, which then gets converted into an incident."
"The AI component allows you to check previous cases and diagnose problems easily."
"Moogsoft is easily deployable and ready to use."
"The product currently seems to be a few steps ahead of the competition."
"I find the unsupervised learning algorithms for noise reduction particularly valuable. The algorithm's ability to identify and reduce noise is a feature we initially liked. The anomaly detection feature is excellent for maintaining system uptime as it helps identify problems quickly."
"The solution is extremely helpful with correlating IP failures and it has a very good sort of flow chart of IP systems. For example, if you see a failure in system A, you can track it down to the system causing the issue. This is a very handy feature."
 

Cons

"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."
"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."
"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."
"The product roadmap doesn't align with our roadmap."
"Some additional API interfacing would be great to enable getting the data out of AIOps programmatically."
"I would like to see how Moogsoft integrates with the multi-cloud and brings out a single pane of glass, to see everything on one screen."
"I would like to see additional reports or information on the dashboard that includes metrics about CPU usage and memory."
"They are very much dependent on open-source technologies like RabbitMQ message bus. They are using open-source databases, Apache Tomcat, NGINX. If we face any issues with Apache Tomcat or the RabbitMQ message bus, then we do not get support from them. We have to troubleshoot it ourselves."
"It is taking a long time to set it up and could do more to roll out quickly."
"Sometimes Moogsoft experiences stability issues due to bugs or internal problems, leading to downtime, which the Mulesoft team addresses."
"The documentation and flexibility for generic integration could be improved."
 

Pricing and Cost Advice

"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."
"The solution is very good from a business impact point of view, but it's quite expensive because it's an enterprise-grade solution."
"Moogsoft's licensing is consumption-based, so the price may increase depending on the environment."
"As for pricing, Moogsoft recently updated their pricing model, and we're still evaluating it. It's an area where clarity is needed with the new alert-based pricing model."
"It's a very cost-effective and competitive product."
"When compared to other solutions, it is quite good."
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Top Industries

By visitors reading reviews
Financial Services Firm
15%
Manufacturing Company
11%
Computer Software Company
11%
Retailer
8%
Financial Services Firm
17%
Computer Software Company
12%
Manufacturing Company
6%
Transportation Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise4
Large Enterprise11
 

Questions from the Community

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...
What do you like most about Moogsoft?
Incident management is streamlined with Moogsoft. One standout feature is its unique situation-creation capability, differentiating it from other fault management tools. While other tools typically...
What needs improvement with Moogsoft?
We can improve Moogsoft by optimizing its noise feature, normalizing events, customizing deduplication rules, enhancing correlation accuracy, and improving incident response and automation. Introdu...
 

Comparisons

 

Overview

 

Sample Customers

Harmoney, Zidisha, ONE Marketing, DonorBureau, Trupanion, Avant
RetailNext
Find out what your peers are saying about DataRobot vs. Moogsoft and other solutions. Updated: September 2025.
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