Compare Cloudera Data Science Workbench vs. RapidMiner
Use Cloudera Data Science Workbench? Share your opinion.
 | RajivSharma Senior Product Manager at CustomerXps Software |
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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:
"The Cloudera Data Science Workbench is customizable and easy to use."
"The documentation for this solution is very good, where each operator is explained with how to use it."
"RapidMiner is very easy to use."
"The most valuable features are the Binary classification and Auto Model."
"The most valuable feature is what the product sets out to do, which is extracting information and data."
"The most valuable feature of RapidMiner is that it can read a large number of file formats including CSV, Excel, and in particular, SPSS."
"Scalability is not really a concern with RapidMiner. It scales very well and can be used in global implementations."
"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."
Cons
"Running this solution requires a minimum of 12GB to 16GB of RAM."
"The price of this solution should be improved."
"I would like to see all users have access to all of the deep learning models, and that they can be used easily."
"RapidMiner would be improved with the inclusion of more machine learning algorithms for generating time-series forecasting models."
"A great product but confusing in some way with regard to the user interface and integration with other tools."
"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."
"I think that they should make deep learning models easier."
"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."
Information Not Available
"I used an educational license for this solution, which is available free of charge."
"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."
"The client only has to pay the licensing costs. There are not any maintenance or hidden costs in addition to the license."
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Top Answer: The Cloudera Data Science Workbench is customizable and easy to use.
Top Answer: Running this solution requires a minimum of 12GB to 16GB of RAM. In the future, I would like to see a student version of the Data Science Workbench that includes sample datasets that can be used for… more »
Top Answer: I am a professor and this is one of the solutions that I use as a teaching tool for my students. The most recent version can be used by the students while they are working in the labs because our… more »
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4,112
Comparisons
3,615
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Average Words per Review
302
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8.0
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9,112
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7,204
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8
Average Words per Review
657
Rating
8.4
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CDSW
Cloudera Data Science Workbench (CDSW) makes secure, collaborative data science at scale a reality for the enterprise and accelerates the delivery of new data products. With CDSW, organizations can research and experiment faster, deploy models easily and with confidence, as well as rely on the wider Cloudera platform to reduce the risks and costs of data science projects. Access any data anywhere – from cloud object storage to data warehouses, CDSW provides connectivity not only to CDH but the systems your data science teams rely on for analysis.
RapidMiner's unified data science platform accelerates the building of complete analytical workflows - from data prep to machine learning to model validation to deployment - in a single environment, improving efficiency and shortening the time to value for data science projects.
Learn more about Cloudera Data Science Workbench
Learn more about RapidMiner
IQVIA, Rush University Medical Center, Western Union
PayPal, Deloitte, eBay, Cisco, Miele, Volkswagen
Computer Software Company30%
Comms Service Provider14%
Financial Services Firm13%
Insurance Company6%
University43%
Energy/Utilities Company14%
Educational Organization14%
Engineering Company14%
Computer Software Company23%
Comms Service Provider21%
University9%
Government6%
No Data Available
Small Business58%
Midsize Enterprise8%
Large Enterprise33%
Small Business31%
Midsize Enterprise3%
Large Enterprise66%
Find out what your peers are saying about Alteryx, Databricks, Knime and others in Data Science Platforms. Updated: March 2021.
475,705 professionals have used our research since 2012.
Cloudera Data Science Workbench is ranked 18th in Data Science Platforms with 1 review while RapidMiner is ranked 7th in Data Science Platforms with 8 reviews. Cloudera Data Science Workbench is rated 8.0, while RapidMiner is rated 8.4. The top reviewer of Cloudera Data Science Workbench writes "Customizable, easy to install, and easy to use". On the other hand, the top reviewer of RapidMiner writes "Offers good tutorials that make it easy to learn and use, with a powerful feature to compare machine learning algorithms". Cloudera Data Science Workbench is most compared with Databricks, Amazon SageMaker, Alteryx, Anaconda and Dremio, whereas RapidMiner is most compared with KNIME, Alteryx, Dataiku Data Science Studio and IBM SPSS Modeler.
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