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Darwin vs Domino Data Science Platform comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 2024

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

Darwin
Ranking in Data Science Platforms
25th
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
8
Ranking in other categories
No ranking in other categories
Domino Data Science Platform
Ranking in Data Science Platforms
17th
Average Rating
7.6
Reviews Sentiment
6.7
Number of Reviews
2
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of March 2026, in the Data Science Platforms category, the mindshare of Darwin is 1.5%, up from 0.3% compared to the previous year. The mindshare of Domino Data Science Platform is 2.2%, down from 2.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Domino Data Science Platform2.2%
Darwin1.5%
Other96.3%
Data Science Platforms
 

Featured Reviews

AC
Founder at Helio Summit
Empowers SMEs to build solutions and interface them with the existing business systems, products and workflows.
There's always room for improvement in the UI and continuing to evolve it to do everything that the rest of AI can do. Because it's so much better than traditional methods, we don't get a ton of complaints of, "Oh, we wish we could do that." Most people are happy to see that they can build models that quickly, and that it can be done by the people who actually understand the problem, i.e. SMEs, rather than having to rely on data scientists. There's a small learning curve, but it's shorter for an SME in a given industry to learn Darwin than it takes for data scientists to learn industry-specific problems. The industry I work in deals with tons and tons of data and a lot of it lends itself to Darwin-created solutions. Initially, there were some limitations around the size of the datasets, the number of rows and number of columns. That was probably the biggest challenge. But we've seen the Darwin product, over time, slowly remove those limitations. We're happy with the progress they've made.
AS
Machine Learning Engineer at Unemployed
Accelerated machine learning model development with seamless deployment
We used Domino Data Science Platform for developing and working with machine learning models. It facilitated end-to-end development processes. Domino is based on Git, enabling collaboration similar to using Git. Each user operates on their own equivalent of a branch or fork, and once finished, they…

Quotes from Members

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

Pros

"I find it quite simple to use. Once you are trained on the model, you can use it anyway you want."
"The thing that I find most valuable is the ability to clean the data."
"Darwin has increased efficiency and productivity for our company. With our risk management team, there were models that took them more than three days to process each, only to see the outcome. Now, it takes minutes for Darwin to process the current model. So, we can have it in minutes. We don't have to wait three days for all the models to be tested, then make a decision."
"When we have a clean dataset, within two to three hours we have a really nice model, one that is better than we could generate in a week."
"Darwin is the perfect tool to solve this issue; what the machine-learning industry needs at this point to expand exponentially in the oil and gas market."
"We have managed to reduce the percentage of high-risk clients from 8.9 percent to 5 percent, which is very significant in the overall quality of our clients and very good news for everyone, especially our investors."
"Due to the predictions that we have been able to do because of the use of Darwin, we have decreased our delinquency index from almost nine percent to five percent and reduced our client loss index from 19 percent to 10 percent."
"Even people who are not fully technical can use it with a little guidance or something."
"The scalability of the solution is good; I'd rate it four out of five."
"We primarily use the solution for customer retention, but there are a lot of use cases for this particular product."
"The workspaces, which are like wrappers of Docker containers, made it easy to start development environments using Domino."
 

Cons

"The license cost is not cheap, especially not for markets like Mexico."
"Our main data repository is on AWS. The trouble we are having is that we have to download the data from our repository to bring it into Darwin. It would be great if there was an API to connect our repository to Darwin."
"There's always room for improvement in the UI and continuing to evolve it to do everything that the rest of AI can do."
"Because so much is done under the hood of Darwin, it is hard to trust how it gets the answers it gets."
"The analyze function takes a lot of time."
"In the beginning, when we started to see how Darwin works, we thought that maybe, from raw, dirty data, we could generate a model really fast, but that's not true."
"We have used Darwin as a complement to other tools like R and SPSS to get the accuracy we want."
"The Read Me's and the tutorials need to be greatly improved to get customers to understand how things work. It might be helpful to have some sample data sets for people to play around with, as well as some tutorial videos. It was very hard to find information on this in the time crunch that we had, to see how it worked and then make it work, while interfacing with folks at SparkCognition."
"The predictive analysis feature needs improvement."
"The predictive analysis feature needs improvement."
"The deployment of large language models (LLMs) could be improved."
 

Pricing and Cost Advice

"I believe our cost is $1,000 per month."
"As far as I understand, my company is not paying anything to use the product."
"The license cost is not cheap, especially not for markets like Mexico. But sometimes, you do have to make these leap of faith for some tools to see if they can get you the disruption that you are aiming for. The investment has paid off for us very well."
"In just six months, we calculated six million pesos that we have prevented in revenue from going away with another customer because of this solution. Thanks to Darwin, we didn't lose those six million pesos."
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Top Industries

By visitors reading reviews
No data available
Financial Services Firm
37%
Manufacturing Company
8%
Insurance Company
8%
Healthcare Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business6
Large Enterprise2
No data available
 

Questions from the Community

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What needs improvement with Domino Data Science Platform?
The deployment of large language models (LLMs) could be improved. Currently, Domino provides a simple server that cannot handle big deployments, which is not suitable for LLMs.
What is your primary use case for Domino Data Science Platform?
We used Domino Data Science Platform for developing and working with machine learning models. It facilitated end-to-end development processes. Domino is based on Git, enabling collaboration similar...
What advice do you have for others considering Domino Data Science Platform?
It's important to have a DevOps team well-versed with cloud-native solutions to manage Domino effectively. Relying solely on data scientists might not be sufficient. I'd rate the solution eight out...
 

Also Known As

No data available
Domino Data Lab Platform
 

Interactive Demo

Demo not available
 

Overview

 

Sample Customers

Hunt Oil, Hitachi High-Tech Solutions
Allstate, GSK, AstraZeneca, Federal Reserve, US Navy, Bristol Myers Squibb, Bayer, BNP Paribas, Moodys, New York Life
Find out what your peers are saying about Darwin vs. Domino Data Science Platform and other solutions. Updated: March 2026.
884,933 professionals have used our research since 2012.