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Darwin vs IBM SPSS Modeler 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
26th
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
8
Ranking in other categories
No ranking in other categories
IBM SPSS Modeler
Ranking in Data Science Platforms
16th
Average Rating
8.0
Reviews Sentiment
6.3
Number of Reviews
40
Ranking in other categories
Data Mining (3rd)
 

Mindshare comparison

As of October 2025, in the Data Science Platforms category, the mindshare of Darwin is 0.5%, up from 0.3% compared to the previous year. The mindshare of IBM SPSS Modeler is 3.5%, up from 2.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Market Share Distribution
ProductMarket Share (%)
IBM SPSS Modeler3.5%
Darwin0.5%
Other96.0%
Data Science Platforms
 

Featured Reviews

AC
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.
PeterHuo - PeerSpot reviewer
Good tool for extracting data from data warehouses, creating streams, and manipulating logic to extract final data
There are performance issues. Extracting data from many combined tables can take hours and occasionally crash the server due to memory leaks. This performance problem bothers people. The performance issue seems to be related to the server. We design streams on the client and submit them to the server, which generates a large SQL statement. There are two potential bottlenecks: one in the server and another in data extraction. I'm unsure about the exact mechanics of data splitting when fetching from the database. When streams become larger, performance bottlenecks may occur in the IBM SPSS Modeler server or the database. Sometimes the server crashes and needs to be restarted to release memory on both sides. I'm not sure exactly where the problem is caused, as I focus on stream design rather than server issues. The problem could be on the IBM SPSS Modeler server and database.

Quotes from Members

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

Pros

"The thing that I find most valuable is the ability to clean the data."
"I find it quite simple to use. Once you are trained on the model, you can use it anyway you want."
"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."
"The solution helps with the automatic assessment of the quality of datasets, such as missing data points or incorrect data types."
"In terms of streamlining a lot of the low-level data science work, it does a few things there."
"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 liked the data checking feature where it looks at your data and sees how viable it is for use. That's a really cool feature. Automatic assessment of the quality of datasets, to me, seems very valuable."
"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."
"It continues to be a very flexible platform, so that it handles R and Python and other types of technology. It seems to be growing with additional open-source movement out there on different platforms."
"Automation is great and this product is very organized."
"It will scale up to anything we need."
"The visual modeling capability is one of its attractive features."
"It's very easy to use. The drag and drop feature makes it very easy when you are building and testing the streams. That's very useful."
"New algorithms are added into every version of Modeler, e.g., SMOTE, random forest, etc. The Derive node is used for the syntax code to derive the data."
"It makes pretty good use of memory. There are algorithms take a long time to run in R, and somehow they run more efficiently in Modeler."
"We have integration where you can write third-party apps. This sort of feature opens it up to being able to do anything you want."
 

Cons

"The analyze function takes a lot of time."
"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."
"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 are issues around the ethics of artificial intelligence and machine learning. You need to have a lot of transparency regarding what is going on under the hood in order to trust it. Because so much is done under the hood of Darwin, it is hard to trust how it gets the answers it gets."
"There's always room for improvement in the UI and continuing to evolve it to do everything that the rest of AI can do."
"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."
"Something they are working on, which is great, is to have an API that can access data directly from the source. Currently, we have to create a specific dataset for each model."
"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."
"C&DS will not meet our scalability needs."
"​Initial setup of the software was complex, because of our own problems within the government."
"Time Series or forecasting needs to be easier. It is a very important feature, and it should be made easier and more automated to use. For instance, for logistic regression, binary or multinomial is used automatically based on the type of the target variable. I wish they can make Time Series easier to use in a similar way."
"The biggest issue with the visual modeling capability is that we can't extract the SQL code under the hood."
"If IBM could add some of the popular models into the SPSS for further analysis, like popular regression models, I think that would be a helpful improvement."
"It is not integrated with Qlik, Tableau, and Power BI."
"The forecasting could be a bit easier."
"​I would like better integration into the Weather Company solution. I have raised a couple of concerns about this integration and having more time series capabilities.​"
 

Pricing and Cost Advice

"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."
"I believe our cost is $1,000 per month."
"Its price is okay for a company, but for personal use, it is considered somewhat expensive."
"I am using the free version of IBM SPSS Modeler, it is the educational edition version."
"The scalability was kind of limited by our ability to get other people licenses, and that was usually more of a financial constraint. It's expensive, but it's a good tool."
"It got us a good amount of money with quick and efficient modeling."
"If you are in a university and the license is free then you can use the tool without any charges, which is good."
"Having in mind all four tools from Garner’s top quadrant, the pricing of this tool is competitive and it reflects the quality that it offers."
"It is a huge increase to time savings."
"This tool, being an IBM product, is pretty expensive."
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Top Industries

By visitors reading reviews
No data available
Financial Services Firm
12%
Government
11%
Educational Organization
10%
University
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business6
Large Enterprise2
By reviewers
Company SizeCount
Small Business9
Midsize Enterprise4
Large Enterprise32
 

Questions from the Community

Ask a question
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What do you like most about IBM SPSS Modeler?
Compared to other tools, the product works much easier to analyze data without coding.
What is your experience regarding pricing and costs for IBM SPSS Modeler?
The government has funds and a budget, it's hard to say if it's expensive or cheap. In Canada, they have a yearly budget. They used to encourage people to use the modeler for development. If ten us...
What needs improvement with IBM SPSS Modeler?
The customer comes to you and says they want to deploy it and make a production out of this, which is very difficult and expensive with IBM SPSS Modeler. With MATLAB, there is no problem. I have a ...
 

Also Known As

No data available
SPSS Modeler
 

Overview

 

Sample Customers

Hunt Oil, Hitachi High-Tech Solutions
Reisebªro Idealtours GmbH, MedeAnalytics, Afni, Israel Electric Corporation, Nedbank Ltd., DigitalGlobe, Vodafone Hungary, Aegon Hungary, Bureau Veritas, Brammer Group, Florida Department of Juvenile Justice, InSites Consulting, Fortis Turkey
Find out what your peers are saying about Darwin vs. IBM SPSS Modeler and other solutions. Updated: September 2025.
869,566 professionals have used our research since 2012.