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Coralogix vs DataRobot comparison

 

Comparison Buyer's Guide

Executive Summary

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

Coralogix
Ranking in AI Observability
18th
Average Rating
8.4
Reviews Sentiment
6.6
Number of Reviews
13
Ranking in other categories
Application Performance Monitoring (APM) and Observability (21st), Log Management (21st), Security Information and Event Management (SIEM) (22nd), API Management (15th), Streaming Analytics (15th), Anomaly Detection Tools (1st)
DataRobot
Ranking in AI Observability
66th
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
6
Ranking in other categories
Predictive Analytics (5th), AI Development Platforms (15th), AIOps (15th), AI Finance & Accounting (4th)
 

Mindshare comparison

As of January 2026, in the AI Observability category, the mindshare of Coralogix is 2.6%, down from 4.4% compared to the previous year. The mindshare of DataRobot is 0.6%, down from 1.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Observability Market Share Distribution
ProductMarket Share (%)
Coralogix2.6%
DataRobot0.6%
Other96.8%
AI Observability
 

Featured Reviews

Naveenkumar Lakshman - PeerSpot reviewer
Presales Engineer at Crayon AS
Centralized monitoring has improved real-time issue tracking and reduced root cause analysis time
One of the best features that Coralogix offers is that it is integration friendly. I can seamlessly work with different cloud providers including AWS, Azure, and GCP. I can monitor Kubernetes or Docker platforms as well, and I can integrate with the DevOps chain including Jenkins and all infrastructure code, Terraform, or Ansible. Coralogix has positively impacted my organization by providing a centralized console to monitor the dashboard, giving me rich flexibility to see different sorts of data that is spread across the logs, metrics, or traces, which are the typical pillars of the observability tool. I have the interface where I can use the drag-and-drop feature, and I can create different types of charts. Mainly, I have the line charts and time series ones that I generally use in many use cases, gauges, tables, pie charts, or markdown widgets. These are the ones generically available, and I can switch between the visualization types. I am getting the underlying query in that and can import and export dashboards built upon the JSON format. I can have my own APIs integrated with my dashboards as well, such as with Terraform, which is useful for scaling across my environments. Regarding root cause analysis, mainly what I can do is correlate across all of the layers because the main logs that I work on are storage-related, including CIFS, NFS, SAN traffic, and the metrics including storage, throughput, or VM resource usage. Being able to view logs, metrics, or traces available, I get all of these in one place, and I can do root cause analysis much quicker.
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.

Quotes from Members

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

Pros

"The most valuable feature of Coralogix is that it is a very good vendor for metrics."
"A non-tech person can easily get used to it."
"The best feature of this solution allows us to correlate logs, metrics and traces."
"The log monitoring is good, and the dashboards that we create are beneficial."
"The solution offers very good convenience filtering."
"The initial setup is straightforward."
"Coralogix scales well, and I will rate it nine out of ten."
"The solution is easy to use and to start with."
"Tasks such as model testing, feature engineering, and predictions that used to take us days or weeks can now be accomplished in hours."
"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."
"By automating highly technical aspects like model comparison, DataRobot enhances productivity and reduces project timelines from three months to less than one month."
"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

"Coralogix's dashboard and search capabilities do not help me in any particular way."
"We want it to work at what it is expected to work at and not really based on the updated configuration which one developer has decided to change."
"Coralogix should have some AI capabilities to auto-detect anomalies and provide suggestions. The increasing volume of data and the resulting bandwidth charges are concerns."
"Maybe they could make it more user-friendly."
"It would be helpful if Coralogix could integrate the main modules that any organization requires into a single subscription."
"From my experience, Coralogix has horrible Terraform providers."
"The customizable dashboards haven't really helped with my company's efficiency at all, and I think there's room for improvement."
"Coralogix should have some AI capabilities to auto-detect anomalies and provide suggestions."
"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."
"There is a lack of transparency in the models; sometimes it feels like a black box."
"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 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."
"Generative AI has taken pace, and I would like to see how DataRobot assists in doing generative AI and large language models."
 

Pricing and Cost Advice

"Currently, we are at a very minimal cost, which is around $400 per month since we have reduced our usage. Initially, we were at $900 per month."
"We are paying roughly $5,000 a month."
"The cost of the solution is per volume of data ingested."
"The platform has a reasonable cost. I rate the pricing a three out of ten."
"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
Financial Services Firm
10%
Computer Software Company
10%
Manufacturing Company
8%
Comms Service Provider
6%
Financial Services Firm
14%
Manufacturing Company
12%
Computer Software Company
10%
Retailer
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business8
Midsize Enterprise2
Large Enterprise5
No data available
 

Questions from the Community

What do you like most about Coralogix?
Numerous data monitoring tools are available, but Coralogix somehow fine-tunes our policies and effectively supports our teams.
What is your experience regarding pricing and costs for Coralogix?
To monitor and manage costs associated with Coralogix, I analyze my trend, looking at how the data is being ingested. Generally, it is charged based on what we store, and therefore there are certai...
What needs improvement with Coralogix?
I think Coralogix can be improved with flexible dashboards. Creating specific views, such as saving a dev environment as a separate view rather than adding filters every time, would be great.
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...
 

Comparisons

 

Overview

 

Sample Customers

Payoneer, AGS, Monday.com, Capgemini
Harmoney, Zidisha, ONE Marketing, DonorBureau, Trupanion, Avant
Find out what your peers are saying about Coralogix vs. DataRobot and other solutions. Updated: December 2025.
881,114 professionals have used our research since 2012.