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Anaconda vs Cloudera Data Science Workbench comparison

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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 is excellent and the solution has a very large and active community that supports it.""With Anaconda Navigator, we have been able to use multiple IDEs such as JupyterLab, Jupyter Notebook, Spyder, Visual Studio Code, and RStudio in one place. The platform-agnostic package manager, "Conda", makes life easy when it comes to managing and installing packages.""The product is responsive, sleek and has a beautiful interface that is pleasant to use. It helps users to easily share code.""It's interesting. It's user friendly. That's what makes it outstanding among the others. It has a collection of R, Python, and others. Their platform strategy has a collection of many other visualization tools, apart from Spyder and RStudio, which is really helpful for data science. For any data science professional, Anaconda is really handy. It has almost all the tools for data science."

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"The Cloudera Data Science Workbench is customizable and easy to use."

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Cons
"When you install Anaconda for the first time, it's really difficult to update it.""Anaconda should be optimized for RAM consumption.""It crashes once in a while. In case of a reboot or something unexpected, the unseen code part will get diminished, and it relatively takes longer than other applications when a reboot is happening. They can improve in these areas. They can also bring some database software. They have software for analytics and virtualization. However, they don't have any software for the database.""One thing that hurts the product is that the company is not doing more to advertise it as a solution and make it more well known."

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"Running this solution requires a minimum of 12GB to 16GB of RAM."

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Pricing and Cost Advice
  • "The product is open-source and free to use."
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    Questions from the Community
    Top Answer: 
    With Anaconda Navigator, we have been able to use multiple IDEs such as JupyterLab, Jupyter Notebook, Spyder, Visual Studio Code, and RStudio in one place. The platform-agnostic package manager… more »
    Top Answer: 
    With Anaconda Navigator, we have been able to use multiple IDEs such as JupyterLab, Jupyter Notebook, Spyder, Visual Studio Code, and RStudio in one place. The platform-agnostic package manager… more »
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    Ranking
    11th
    Views
    5,552
    Comparisons
    4,680
    Reviews
    3
    Average Words per Review
    523
    Rating
    9.3
    15th
    Views
    3,643
    Comparisons
    3,100
    Reviews
    1
    Average Words per Review
    302
    Rating
    8.0
    Comparisons
    Also Known As
    CDSW
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    Overview

    Anaconda makes it easy for you to install and maintain Python environments. Our development team tests to ensure compatibility of Python packages in Anaconda. We support and provide open source assurance for packages in Anaconda to mitigate your risk in using open source and meet your regulatory compliance requirements.

    Python is the fastest growing language for data science. Anaconda includes 720+ Python open source packages and now includes essential R packages. This powerful combination allows you to do everything you want from BI to advanced modeling on complex Big Data

    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.

    Offer
    Learn more about Anaconda
    Learn more about Cloudera Data Science Workbench
    Sample Customers
    LinkedIn, NASA, Boeing, JP Morgan, Recursion Pharmaceuticals, DARPA, Microsoft, Amazon, HP, Cisco, Thomson Reuters, IBM, Bridgestone
    IQVIA, Rush University Medical Center, Western Union
    Top Industries
    REVIEWERS
    Financial Services Firm22%
    Manufacturing Company22%
    Non Tech Company11%
    Pharma/Biotech Company11%
    VISITORS READING REVIEWS
    Computer Software Company23%
    Comms Service Provider18%
    Financial Services Firm13%
    Government7%
    VISITORS READING REVIEWS
    Computer Software Company26%
    Financial Services Firm18%
    Comms Service Provider14%
    Insurance Company5%
    Company Size
    REVIEWERS
    Small Business38%
    Large Enterprise63%
    No Data Available
    Find out what your peers are saying about Alteryx, Databricks, Knime and others in Data Science Platforms. Updated: January 2022.
    563,148 professionals have used our research since 2012.

    Anaconda is ranked 11th in Data Science Platforms with 4 reviews while Cloudera Data Science Workbench is ranked 15th in Data Science Platforms with 1 review. Anaconda is rated 9.4, while Cloudera Data Science Workbench is rated 8.0. The top reviewer of Anaconda writes "Responsive, sleek and had a beautiful interface that is pleasant to use". On the other hand, the top reviewer of Cloudera Data Science Workbench writes "Customizable, easy to install, and easy to use". Anaconda is most compared with Databricks, Amazon SageMaker, Microsoft Azure Machine Learning Studio, Microsoft BI and MathWorks Matlab, whereas Cloudera Data Science Workbench is most compared with Databricks, Dataiku Data Science Studio, Amazon SageMaker, Microsoft Azure Machine Learning Studio and Alteryx.

    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.