Altair RapidMiner vs Darwin comparison

Altair and SparkCognition are both solutions in the Data Science Platforms category. Altair is ranked #7 with an average rating of 8.1, while SparkCognition is ranked #26. Altair holds a 7.8% mindshare in Data Science Platforms, compared to SparkCognition’s 0.3% mindshare. Additionally, 96% of Altair users are willing to recommend the solution, compared to 100% of SparkCognition users who would recommend it.

Altair RapidMiner

Read 24 Altair RapidMiner reviews

4,773 Views
745 Comparison Views

96% willing to recommend

Darwin

Read 8 Darwin reviews

298 Views
89 Comparison Views

100% willing to recommend

Altair RapidMiner

Darwin

Comparison Buyer's Guide

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Executive SummaryUpdated on Jun 8, 2025

Altair RapidMiner and Darwin are both leading options in the data analytics and machine learning domain. Altair RapidMiner seems to have the advantage due to its comprehensive features, versatility, and community support, whereas Darwin stands out with its advanced automation capabilities, particularly in predictive analytics.

Features: Altair RapidMiner offers extensive data preparation and machine learning capabilities, generous algorithm support, plus a versatile integration system with various APIs and scripting languages like Python and R. Darwin focuses on efficient deep learning and predictive model automation and provides high accuracy with its model-building features.

Room for Improvement: Altair RapidMiner could enhance its support for evolving AI technologies like generative AI and improve embedding capabilities. Further streamlining of the interface could improve ease of use. Darwin might benefit from an expanded active community and more extensive documentation. Enhanced handling of data type suggestions and redundancy checks could bolster its comprehensiveness.

Ease of Deployment and Customer Service: Altair RapidMiner features both cloud and on-premise deployment options, supported by a vibrant community and extensive resources. Darwin simplifies access with seamless cloud deployment but offers less community interaction, benefiting from automated guidance tools to enhance onboarding.

Pricing and ROI: Altair RapidMiner offers more flexible pricing with scalable costs, promising exceptional long-term ROI through its feature-rich setup. While Darwin requires higher initial investment, it yields significant ROI thanks to its model automation efficiency. RapidMiner’s pricing flexibility invites broader accessibility, contrasted by Darwin’s targeting of high-end analytics in organizations.

To learn more, read our detailed Altair RapidMiner vs. Darwin Report (Updated: June 2025).

Buyer's Guide

Altair RapidMiner vs. Darwin

June 2025

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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

Altair RapidMiner

Ranking in Data Science Platforms

7th

Average Rating

8.6

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Predictive Analytics (2nd)

Darwin

Ranking in Data Science Platforms

26th

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of June 2025, in the Data Science Platforms category, the mindshare of Altair RapidMiner is 7.8%, up from 7.0% compared to the previous year. The mindshare of Darwin is 0.3%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

Rathnam Makam

Senior Technical Manager at a computer software company with 1,001-5,000 employees

A no-code tool that helps to build machine learning models

One challenge I encountered while implementing RapidMiner was the lack of documentation. Since there aren't as many users, finding resources to learn the tool was initially difficult. To overcome this hurdle, I believe RapidMiner could improve by providing more tutorials tailored for new users. I haven't explored the tool's latest version, so I'm unaware of the current features. However, I think it would be beneficial if they could enhance capabilities related to deep neural networks, provide better support for generating UI, and allow for importing and utilizing large language models.

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AaronCooke

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.

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Quotes from Members

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

Pros

"The documentation for this solution is very good, where each operator is explained with how to use it."

"Altair RapidMiner is easy to use and intuitive with no coding required, making it a low code tool."

"The most valuable feature of RapidMiner is that it is code free. It is similar to playing with Lego pieces and executing after you are finished to see the results. Additionally, it is easy to use and has interesting utilities when preparing the data. It has a utility to automatically launch a series of models and show the comparisons. When finished with the comparisons you can select the best one, and deploy it automatically."

"Using the GUI, I can have models and algorithms drag and drop nodes."

"One of the most valuable features is the built-in data tuning feature. Once the model is built, we often struggle to increase its accuracy, but RapidMiner allows us to fine-tune variables. For Example, when working on a project, we can adjust the number of nodes or the depth of trees to see how accuracy changes. This flexibility lets us achieve higher accuracy compared to traditional automated machine-learning models"

"The best part of RapidMiner is efficiency."

"The GUI capabilities of the solution are excellent. Their Auto ML model provides for even non-coder data scientists to deploy a model."

"It's helpful if you want to make informed decisions using data. We can take the information, tease out the attributes, and label everything. It's suitable for profiling and forecasting in any industry."

More Altair RapidMiner pros

"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."

"I find it quite simple to use. Once you are trained on the model, you can use it anyway you want."

"The solution helps with the automatic assessment of the quality of datasets, such as missing data points or incorrect data types."

"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."

"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."

"In terms of streamlining a lot of the low-level data science work, it does a few things there."

"The thing that I find most valuable is the ability to clean the data."

"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."

Cons

"Improve the online data services."

"In terms of the UI and SaaS, the user interface with KNIME is more appealing than RapidMiner."

"It would be helpful to have some tutorials on communicating with Python."

"The visual interface could use something like the-drag-and-drop features which other products already support. Some additional features can make RapidMiner a better tool and maybe more competitive."

"RapidMiner would be improved with the inclusion of more machine learning algorithms for generating time-series forecasting models."

"The server product has been getting updated and continues to be better each release. When I started using RapidMiner, it was solid but not easy to set up and upgrade."

"The price of this solution should be improved."

"The biggest problem, not from a platform process, but from an avoidance process, is when you work in a heavily regulated environment, like banking and finance. Whenever you make a decision or there is an output, you need to bill it as an avoidance to the investigator or to the bank audit team. If you made decisions within this machine learning model, you need to explain why you did so. It would better if you could explain your decision in terms of delivery. However, this is an issue with all ML platforms. Many companies are working heavily in this area to help figure out how to make it more explainable to the business team or the regulator."

More Altair RapidMiner cons

"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."

"The analyze function takes a lot of time."

"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."

"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."

"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."

"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."

"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."

"There's always room for improvement in the UI and continuing to evolve it to do everything that the rest of AI can do."

Pricing and Cost Advice

"I'm not fully aware of RapidMiner's price because we had licenses provided, but from my analysis, it's moderately priced, not too high or too low. It's worth the investment."

"I used an educational license for this solution, which is available free of charge."

"The client only has to pay the licensing costs. There are not any maintenance or hidden costs in addition to the license."

"Although we don't pay licensing fees because it is being used within the university, my understanding is that the cost is between $5,000 and $10,000 USD per year."

"For the university, the cost of the solution is free for the students and teachers."

"As far as I understand, my company is not paying anything to use the product."

"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."

"I believe our cost is $1,000 per month."

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Top Industries

By visitors reading reviews

University

11%

Computer Software Company

11%

Educational Organization

10%

Financial Services Firm

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about RapidMiner?

RapidMiner is a no-code machine learning tool. I can install it on my local machine and work with smaller datasets. It can also connect to databases, allowing me to build models directly on the dat...

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What is your experience regarding pricing and costs for RapidMiner?

I started with a trial version. We are likely to purchase a license, which may offer additional features.

See all answers

What needs improvement with RapidMiner?

Currently, I am unsure of all the AI features available in Altair RapidMiner, particularly advanced AI capabilities like neural networks and deep learning. It would be beneficial if the platform co...

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Comparisons

KNIME vs Altair RapidMiner

Compared 51% of the time

Dataiku vs Altair RapidMiner

Compared 16% of the time

Tableau vs Altair RapidMiner

Compared 7% of the time

Alteryx vs Altair RapidMiner

Compared 7% of the time

IBM SPSS Modeler vs Altair RapidMiner

Compared 3% of the time

More Altair RapidMiner Competitors

Databricks vs Darwin

Compared 50% of the time

IBM Watson Studio vs Darwin

Compared 50% of the time

More Darwin Competitors

Product Reports

Buyer's Guide

Altair RapidMiner

June 2025

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Buyer's Guide

Darwin

June 2025

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Overview

Altair RapidMiner is a leading platform for data science and machine learning, offering a user-friendly interface with powerful tools for predictive analytics. It supports integration with APIs, Python, and cloud services for streamlined workflow creation.

RapidMiner provides an efficient data science environment featuring drag-and-drop functionality, automation tools, and a wide array of algorithms, making it adaptable for novices and experts alike. Users benefit from easy data preparation and analysis alongside robust support from a vibrant community. Challenges include better onboarding and deep learning model accessibility, alongside calls for enhanced image processing and large language model integration.

What features make Altair RapidMiner stand out?

Data science tools: Facilitates machine learning and predictive analytics.
Code-optional GUI: Enables non-programmers to create workflows seamlessly.
Integration: Supports APIs, Python, and cloud services.
Drag-and-drop functionality: Simplifies workflow creation for users.
Algorithm variety: Offers diverse methods for data analysis.

What benefits and ROI should users consider when evaluating?

Efficiency: Saves time in data preparation and workflow automation.
Accessibility: Intuitive design aids beginners and experts.
Community: Access to extensions and collaborative resources.
Documentation: Comprehensive tutorials enhance learning.

Altair RapidMiner is extensively used in business and academia, facilitating tasks like predictive analytics, segmentation, and deployment. In education, it supports data science teaching and research, while in industries such as telecom, banking, and healthcare, it's used for data mining, decision trees, and market analysis.

Altair

SparkCognition builds leading artificial intelligence solutions to advance the most important interests of society. We help customers analyze complex data, empower decision making, and transform human and industrial productivity with award-winning machine learning technology and expert teams focused on defense, IIoT, and finance.

SparkCognition

Sample Customers

PayPal, Deloitte, eBay, Cisco, Miele, Volkswagen

Hunt Oil, Hitachi High-Tech Solutions

Buyer's Guide

Altair RapidMiner vs. Darwin

June 2025

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