Cloudera Data Science Workbench vs Dataiku Data Science Studio comparison

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Executive Summary

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

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Featured Review
Ismail Peer
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 the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person.""Data Science Studio's data science model is very useful.""Cloud-based process run helps in not keeping the systems on while processes are running.""Extremely easy to use with its GUI-based functionality and large compatibility with various data sources. Also, maintenance processes are much more automated than ever, with fewer errors.""The most valuable feature of this solution is that it is one tool that can do everything, and you have the ability to very easily push your design to prediction.""The solution is quite stable.""The most valuable feature is the set of visual data preparation tools."

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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."

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"The ability to have charts right from the explorer would be an improvement.""I think it would help if Data Science Studio added some more features and improved the data model.""The interface for the web app can be a bit difficult. It needs to have better capabilities, at least for developers who like to code. This is due to the fact that everything is enabled in a single window with different tabs. For them to actually develop and do the concurrent testing that needs to be done, it takes a bit of time. That is one improvement that I would like to see - from a web app developer perspective.""In the next release of this solution, I would like to see deep learning better integrated into the tool and not simply an extension or plugin.""Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days).""There were stability issues: 1) SQL operations, such as partitioning, had bugs and showed wrong results. 2) Due to server downtime, scheduled processes used to fail. 3) Access to project folders was compromised (privacy issue) with wrong people getting access to confidential project folders.""I find that it is a little slow during use. It takes more time than I would expect for operations to complete.""Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."

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Pricing and Cost Advice
  • "The annual licensing fees are approximately €20 ($22 USD) per key for the basic version and €40 ($44 USD) per key for the version with everything."
  • More Dataiku Data Science Studio Pricing and Cost Advice →

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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:Data Science Studio's data science model is very useful.
    Top Answer:I think it would help if Data Science Studio added some more features and improved the data model.
    Top Answer:The use case is data science, and we've deployed Data Science Studio in multiple regions for four environments: dev, preset, pre-production, and production.
    Ranking
    17th
    Views
    2,167
    Comparisons
    1,915
    Reviews
    1
    Average Words per Review
    353
    Rating
    6.0
    6th
    Views
    9,361
    Comparisons
    7,285
    Reviews
    1
    Average Words per Review
    190
    Rating
    10.0
    Comparisons
    Also Known As
    CDSW
    Dataiku DSS
    Learn More
    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.

    Dataiku Data Science Studio is the collaborative data science software platform for teams of data scientists, data analysts, and engineers to explore, prototype, build, and deliver their own data products more efficiently.

    Dataiku Data Science Studio is also known as Dataiku DSS. This solution enables you to discover, share, and reuse code and applications so that you can deliver high-quality projects easily and streamline your path to production. As an enterprise leader, you can leverage the power of AI to confidently make business decisions.

    With Dataiku, an intuitive interface is guaranteed and allows users the ability to access and work with data using a point-and-click method. Dataiku analyzes the data to suggest key transformations. Beyond offering 109 data transformation capabilities, Dataiku also includes pipelines that can be generated in SQL which can thereafter be scheduled for automated recomputation.

    What's more, Dataiku allows you to create more than 20 different kinds of charts and also gives you the ability to deploy them into dashboards or create custom web applications for the use of interactive and sophisticated visualization tools.

    In addition, with Dataiku you have the option of using an in-depth statistical analysis, including but not limited to: curves fitting, univariate and bivariate analysis, principal component analysis, correlation analysis, and statistical tests.

    Dataiku Data Science Studio Consists Of:

    • Data preparation
    • Visualization
    • Machine Learning
    • Data Ops
    • ML Ops
    • Analytic Apps

    With Dataiku Data Science Studio You Can:

    • Integrate any data 10x faster
    • Build and automate sophisticated data pipelines
    • Build and share insights in minutes
    • Perform in-depth statistical analysis
    • Create thousands of models to find the best ones
    • Explore and explain models

    Dataiku Data Science Studio Benefits and Features:

    • Use your favorite languages and tools: You can create code working with tools you are already familiar with in the language you prefer (Python, R, SQL, etc.)
    • Easily reuse and share code: This feature helps you reduce inefficiencies and inconsistent data. Dataiku includes project libraries, allowing teams to centralize and share code. Although it comes pre-loaded with starter code for tasks, it also provides you with the ability to add your own code snippets.
    • Simplify complexities related to connecting to data and configuring computer resources: With this feature, data scientists can execute code in both a containerized and distributed way, while also selecting the runtime environment they want. Dataiku works to maintain those containers as well as shut them down when the job is completed.

    Features Users Find Most Valuable:

    • API
    • Reporting/Analytics
    • Third-Party Integrations
    • Data Import/Export
    • Natural Language Processing
    • Search/Filter
    • Monitoring
    • Workflow Management

    Reviews from Real Users

    PeerSpot users note that Dataiku Data Science Studio has a fantastic interface and is also flexible, intuitive, and stable. One user said "I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person." Another user mentioned “The best feature is the user interface. It allows us to see the visual flows.”

    Sample Customers
    IQVIA, Rush University Medical Center, Western Union
    BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
    Top Industries
    VISITORS READING REVIEWS
    Financial Services Firm30%
    Healthcare Company9%
    Computer Software Company9%
    Manufacturing Company7%
    VISITORS READING REVIEWS
    Financial Services Firm18%
    Educational Organization13%
    Manufacturing Company8%
    Computer Software Company8%
    Company Size
    VISITORS READING REVIEWS
    Small Business10%
    Midsize Enterprise12%
    Large Enterprise78%
    VISITORS READING REVIEWS
    Small Business13%
    Midsize Enterprise19%
    Large Enterprise69%
    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.
    768,578 professionals have used our research since 2012.

    Cloudera Data Science Workbench is ranked 17th in Data Science Platforms with 2 reviews while Dataiku Data Science Studio is ranked 6th in Data Science Platforms. Cloudera Data Science Workbench is rated 7.0, while Dataiku Data Science Studio is rated 8.2. 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 Dataiku Data Science Studio writes "The model is very useful". Cloudera Data Science Workbench is most compared with Databricks, Amazon SageMaker, Microsoft Azure Machine Learning Studio, Google Cloud Datalab and Alteryx, whereas Dataiku Data Science Studio is most compared with Databricks, Alteryx, KNIME, Microsoft Azure Machine Learning Studio and Starburst Galaxy.

    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.