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Cloudera Data Science Workbench vs Domino Data Science Platform comparison

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Buyer's Guide
Data Science Platforms
April 2024
Executive Summary

We performed a comparison between Cloudera Data Science Workbench and Domino Data Science Platform 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).
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768,246 professionals have used our research since 2012.
Featured Review
Ismail Peer
Useful for data science modeling but improvement is needed in MLOps and pricing
Syed-Hussain
Good scalability and stability but the predictive analysis feature needs improvement
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"The Cloudera Data Science Workbench is customizable and easy to use.""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."

More Cloudera Data Science Workbench Pros →

"The scalability of the solution is good; I'd rate it four out of five."

More Domino Data Science Platform Pros →

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

More Cloudera Data Science Workbench Cons →

"The predictive analysis feature needs improvement."

More Domino Data Science Platform Cons →

Pricing and Cost Advice
  • "The product is expensive."

    • More Cloudera Data Science Workbench Pricing and Cost Advice →

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    Questions from the Community
    What do you like most about Cloudera Data Science Workbench?
    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 »
    Read all 2 answers   →
    What needs improvement with Cloudera Data Science Workbench?
    Top Answer:The tool's MLOps is not good. It's pricing also needs to improve.
    Read all 2 answers   →
    What is your primary use case for Cloudera Data Science Workbench?
    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 »
    Read all 2 answers   →
    Ask a question

    Earn 20 points

    Ranking
    17th
    out of 53 in Data Science Platforms
    Views
    2,167
    Comparisons
    1,915
    Reviews
    1
    Average Words per Review
    353
    Rating
    6.0
    18th
    out of 53 in Data Science Platforms
    Views
    2,713
    Comparisons
    2,334
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    Comparisons
    Also Known As
    CDSW
    Domino Data Lab Platform
    Learn More
    Cloudera
    Domino Data Lab
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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.

    Domino provides a central system of record that keeps track of all data science activity across an organization. Domino helps data scientists seamlessly orchestrate AWS hardware and software toolkits, increase flexibility and innovation, and maintain required IT controls and standards. Organizations can automatically keep track of all data, tools, experiments, results, discussion, and models, as well as dramatically scale data science investments and impact decision-making across divisions. The platform helps organizations work faster, deploy results sooner, scale rapidly, and reduce regulatory and operational risk.

    Sample Customers
    IQVIA, Rush University Medical Center, Western Union
    Allstate, Tesla, Dell, Moody's Analytics, SurveyMonkey, Eventbrite, Carnival
    Top Industries
    VISITORS READING REVIEWS
    Financial Services Firm30%
    Healthcare Company9%
    Computer Software Company9%
    Manufacturing Company7%
    VISITORS READING REVIEWS
    Financial Services Firm29%
    Insurance Company11%
    Manufacturing Company10%
    Computer Software Company8%
    Company Size
    VISITORS READING REVIEWS
    Small Business10%
    Midsize Enterprise12%
    Large Enterprise78%
    VISITORS READING REVIEWS
    Small Business9%
    Midsize Enterprise7%
    Large Enterprise85%
    Buyer's Guide
    Data Science Platforms
    April 2024
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    768,246 professionals have used our research since 2012.

    Cloudera Data Science Workbench is ranked 17th in Data Science Platforms with 2 reviews while Domino Data Science Platform is ranked 18th in Data Science Platforms. Cloudera Data Science Workbench is rated 7.0, while Domino Data Science Platform is rated 7.0. 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 Domino Data Science Platform writes "Good scalability and stability but the predictive analysis feature needs improvement". Cloudera Data Science Workbench is most compared with Databricks, Amazon SageMaker, Microsoft Azure Machine Learning Studio, Dataiku Data Science Studio and H2O.ai, whereas Domino Data Science Platform is most compared with Databricks, Amazon SageMaker, Microsoft Azure Machine Learning Studio and Dataiku Data Science 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.