Compare Anaconda vs. Cloudera Data Science Workbench

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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
"It helped us find find the optimal area for where our warehouse should be located.""The best part of Anaconda is the media distribution that comes as part of it. It gets us started very quickly.""The most advantageous feature is the logic building.""The solution is stable.""The notebook feature is an improvement over RStudio.""The most valuable feature is the set of libraries that are used to support the functionality that we require.""The most valuable feature is the Jupyter notebook that allows us to write the Python code, compile it on the fly, and then look at the results.""The virtual environment is very good."

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

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Cons
"I think better documentation or a step-by-step guide for installation would help, especially for on-premise users.""The ability to schedule scripts for the building and monitoring of jobs would be an advantage for this platform.""The interface could be improved. Other solutions, like Visual Studio, have much better UI.""One feature that I would like to see is being able to use a different language in a different cell, which would allow me to mix R and Python together.""I think that the framework can be improved to make it easier for people to discover and use things on their own.""Having a small guide or video on the tool would help learn how to use it and what the features are.""The solution would benefit from offering more automation.""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 licensing costs for Anaconda are reasonable.""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: The solution's support is important and needs to be better. I don't have the last update due to the fact that when I tried to update it I had an error and ran into issues. It's not just me; lots of… more »
Top Answer: In Anaconda, we get everything: RStudio, Spyder, and Jupyter. R Studio is for R, and Spyder and Jupyter are for Python. Using these, we will be doing data wrangling and data modeling for a developing… more »
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Ranking
6th
Views
5,192
Comparisons
4,196
Reviews
11
Average Words per Review
470
Rating
7.8
16th
Views
4,064
Comparisons
3,542
Reviews
1
Average Words per Review
302
Rating
8.0
Popular 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 Firm25%
Manufacturing Company25%
Non Tech Company13%
Pharma/Biotech Company13%
VISITORS READING REVIEWS
Computer Software Company21%
Comms Service Provider18%
Financial Services Firm12%
Government7%
VISITORS READING REVIEWS
Computer Software Company29%
Financial Services Firm15%
Comms Service Provider13%
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: June 2021.
512,711 professionals have used our research since 2012.

Anaconda is ranked 6th in Data Science Platforms with 12 reviews while Cloudera Data Science Workbench is ranked 16th in Data Science Platforms with 1 review. Anaconda is rated 7.8, 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 Amazon SageMaker, Databricks, Microsoft Azure Machine Learning Studio, Microsoft BI and MathWorks Matlab, whereas Cloudera Data Science Workbench is most compared with Databricks, Amazon SageMaker, Dataiku Data Science Studio, Alteryx and KNIME.

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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.