Cloudera Data Science Workbench vs RapidMiner comparison

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Cloudera Logo
2,070 views|1,837 comparisons
66% willing to recommend
RapidMiner Logo
5,569 views|4,500 comparisons
95% willing to recommend
Comparison Buyer's Guide
Executive Summary

We performed a comparison between Cloudera Data Science Workbench and RapidMiner based on real PeerSpot user reviews.

Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms.
To learn more, read our detailed Data Science Platforms Report (Updated: April 2024).
770,292 professionals have used our research since 2012.
Featured Review
Ismail Peer
Anonymous User
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"I appreciate CDSW's ability to logically segregate environments, such as data, DR, and production, ensuring they don't interfere with each other. The deployment of machine learning is fast and easy to manage. Its API calls are also fast.""The Cloudera Data Science Workbench is customizable and easy to use."

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"I like not having to write all solutions from code. Being able to drag and drop controls, enables me to focus on building the best model, without needing to search for syntax errors or extra libraries.""The GUI capabilities of the solution are excellent. Their Auto ML model provides for even non-coder data scientists to deploy a model.""What I like about RapidMiner is its all-in-one nature, which allows me to prepare, extract, transform, and load data within the same tool.""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.""The most valuable features are the Binary classification and Auto Model.""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.""It is easy to use and has a huge community that I can rely on for help. Moreover, it is interactive.""I've been using a lot of components from the Strategic Extension and Python Extension."

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Cons
"Running this solution requires a minimum of 12GB to 16GB of RAM.""The tool's MLOps is not good. It's pricing also needs to improve."

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"I would like to see all users have access to all of the deep learning models, and that they can be used easily.""Many things in the interface look nice, but they aren't of much use to the operator. It already has lots of variables in there.""RapidMiner would be improved with the inclusion of more machine learning algorithms for generating time-series forecasting models.""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.""I would like to see more integration capabilities.""In terms of the UI and SaaS, the user interface with KNIME is more appealing than RapidMiner.""A great product but confusing in some way with regard to the user interface and integration with other tools.""Improve the online data services."

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Pricing and Cost Advice
  • "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."
  • "For the university, the cost of the solution is free for the students and teachers."
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    Questions from the Community
    Top Answer:I appreciate CDSW's ability to logically segregate environments, such as data, DR, and production, ensuring they don't interfere with each other. The deployment of machine learning is fast and easy to… more »
    Top Answer:The tool's MLOps is not good. It's pricing also needs to improve.
    Top Answer:We have different use cases. Our banking use case uses machine learning to identify customer life events and recommend the best-suited card products. These machine-learning models are deployed in our… more »
    Top Answer:What I like about RapidMiner is its all-in-one nature, which allows me to prepare, extract, transform, and load data within the same tool.
    Top Answer:I would appreciate improvements in automation and customization options to further streamline processes. Additionally, it can be challenging to structure formulas and access certain metrics, requiring… more »
    Ranking
    18th
    Views
    2,070
    Comparisons
    1,837
    Reviews
    1
    Average Words per Review
    353
    Rating
    6.0
    6th
    Views
    5,569
    Comparisons
    4,500
    Reviews
    5
    Average Words per Review
    346
    Rating
    8.2
    Comparisons
    Also Known As
    CDSW
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    Overview

    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.

    Sample Customers
    IQVIA, Rush University Medical Center, Western Union
    PayPal, Deloitte, eBay, Cisco, Miele, Volkswagen
    Top Industries
    VISITORS READING REVIEWS
    Financial Services Firm31%
    Healthcare Company10%
    Computer Software Company8%
    Manufacturing Company7%
    REVIEWERS
    University43%
    Energy/Utilities Company7%
    Educational Organization7%
    Engineering Company7%
    VISITORS READING REVIEWS
    University12%
    Computer Software Company10%
    Educational Organization10%
    Manufacturing Company9%
    Company Size
    VISITORS READING REVIEWS
    Small Business9%
    Midsize Enterprise12%
    Large Enterprise80%
    REVIEWERS
    Small Business48%
    Midsize Enterprise19%
    Large Enterprise33%
    VISITORS READING REVIEWS
    Small Business20%
    Midsize Enterprise13%
    Large Enterprise67%
    Buyer's Guide
    Data Science Platforms
    April 2024
    Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms. Updated: April 2024.
    770,292 professionals have used our research since 2012.

    Cloudera Data Science Workbench is ranked 18th in Data Science Platforms with 2 reviews while RapidMiner is ranked 6th in Data Science Platforms with 19 reviews. Cloudera Data Science Workbench is rated 7.0, while RapidMiner is rated 8.6. The top reviewer of Cloudera Data Science Workbench writes "Useful for data science modeling but improvement is needed in MLOps and pricing ". 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, Microsoft Azure Machine Learning Studio, Dataiku Data Science Studio and Google Cloud Datalab, whereas RapidMiner is most compared with KNIME, Alteryx, Dataiku Data Science Studio, Tableau and Microsoft Azure Machine Learning Studio.

    See our list of best Data Science Platforms vendors.

    We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.