We performed a comparison between Anaconda and Cloudera Data Science Workbench based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."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."
"The solution is stable."
"The documentation is excellent and the solution has a very large and active community that supports it."
"The most advantageous feature is the logic building."
"I can use Anaconda for non-heavy tasks."
"The most valuable feature is the set of libraries that are used to support the functionality that we require."
"It helped us find find the optimal area for where our warehouse should be located."
"The notebook feature is an improvement over RStudio."
"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."
"The ability to schedule scripts for the building and monitoring of jobs would be an advantage for this platform."
"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."
"I think that the framework can be improved to make it easier for people to discover and use things on their own."
"The solution would benefit from offering more automation."
"When you install Anaconda for the first time, it's really difficult to update it."
"Anaconda could benefit from improvement in its user interface to make it more attractive and user-friendly. Currently, it's boring."
"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."
"Anaconda should be optimized for RAM consumption."
"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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Anaconda is ranked 13th in Data Science Platforms with 15 reviews while Cloudera Data Science Workbench is ranked 17th in Data Science Platforms with 2 reviews. Anaconda is rated 7.8, while Cloudera Data Science Workbench is rated 7.0. The top reviewer of Anaconda writes "Offers free version and is helpful to handle small-scale workloads". On the other hand, the top reviewer of Cloudera Data Science Workbench writes "Useful for data science modeling but improvement is needed in MLOps and pricing ". Anaconda is most compared with Databricks, Microsoft Azure Machine Learning Studio, Amazon SageMaker, Microsoft Power BI and IBM SPSS Statistics, whereas Cloudera Data Science Workbench is most compared with Databricks, Amazon SageMaker, Microsoft Azure Machine Learning Studio, Dataiku Data Science Studio and Google Cloud Datalab.
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