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Darwin vs SAP Predictive Analytics 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
SAP Predictive Analytics
Ranking in Data Science Platforms
28th
Average Rating
8.6
Reviews Sentiment
7.1
Number of Reviews
3
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 SAP Predictive Analytics is 1.3%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Darwin1.5%
SAP Predictive Analytics1.3%
Other97.2%
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.
Gary Cook - PeerSpot reviewer
Executive at Empowered Analytics
Enables us to forecast and pull trends and has an easy installation
My rating for SAP Predictive Analytics would be an eight out of ten. If I have to be bold, I'll probably say that we're building away hours, and we are actually putting a lot of the actual predicting stuff back into the warehouse. So running it very bi-directionally. So I'm not sure what its integration features are at the moment, but that's an area we're going to look into in the next month or so.

Quotes from Members

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

Pros

"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."
"The key feature is the automated model-building. It has a good UI that will let people who aren't data scientists get in there and upload datasets and actually start building models, with very little training. They don't need to have any understanding of data science."
"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."
"Even people who are not fully technical can use it with a little guidance or something."
"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."
"The solution helps with the automatic assessment of the quality of datasets, such as missing data points or incorrect data types."
"Darwin is really useful for people who don't necessarily do a lot of data science."
"The most valuable feature is the model-generation. With a nice dataset, Darwin gives you a nice model. That's a really nice feature because, if we're doing that ourselves, it's trial and error; we change the parameters a little and try again. We save time by just giving the dataset to Darwin and letting Darwin generate a model. We find the models it generates are good; better than we can generate."
"I think the features of the actual ability to forecast and pull trends and correlations has been really good."
"SAP Predictive Analytics is better suited for business users because it hides the complexity of the model, whereas Microsoft Azure Machine Learning provides a lot more flexibility for technical professionals to tweak the model."
"I have found that the solution is very stable."
"We always purchase SAP support because it is very good."
"The most valuable features are the analytics and reporting."
 

Cons

"An area where Darwin might be a little weak is its automatic assessment of the quality of datasets. The first results it produces in this area are good, but in our experience, we have found that extra analysis is needed to produce an extra-clean set of data."
"There's always room for improvement in the UI and continuing to evolve it to do everything that the rest of AI can do."
"The license cost is not cheap, especially not for markets like Mexico."
"The analyze function takes a lot of time."
"If you give a lot of data to Darwin, sometimes it can hang."
"The challenge is very big toward making models operational or to industrialize them. E.g., what we want to do is to make unique credit models for each customer. So, we are preparing the types of customers who we can try new credit models on Darwin. But, I see this still very challenging to be able to get the data sets so Darwin can work. At this point, we are working it to get the data sets ready for Darwin."
"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."
"There's always room for improvement in the UI and continuing to evolve it to do everything that the rest of AI can do."
"The license fee appears to be prohibitively expensive and overly secretive, leading our clients to opt for cloud-based solutions that only charge for data storage and processing time."
"This solution works for acquired data but not live, real-time data."
"This solution works for acquired data but not live, real-time data."
 

Pricing and Cost Advice

"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."
"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."
"As far as I understand, my company is not paying anything to use the product."
"I believe our cost is $1,000 per month."
"A free trial version is available for testing out this solution."
"The pricing is reasonable"
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Company Size

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

Also Known As

No data available
SAP BusinessObjects Predictive Analytics, BusinessObjects Predictive Analytics, BOPA
 

Overview

 

Sample Customers

Hunt Oil, Hitachi High-Tech Solutions
mBank
Find out what your peers are saying about Darwin vs. SAP Predictive Analytics and other solutions. Updated: March 2026.
884,933 professionals have used our research since 2012.