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."The product is responsive, sleek and has a beautiful interface that is pleasant to use. It helps users to easily share code."
"The solution is stable."
"The notebook feature is an improvement over RStudio."
"It helped us find find the optimal area for where our warehouse should be located."
"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."
"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 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 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."
"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."
"The interface could be improved. Other solutions, like Visual Studio, have much better UI."
"When you install Anaconda for the first time, it's really difficult to update it."
"I think that the framework can be improved to make it easier for people to discover and use things on their own."
"I think better documentation or a step-by-step guide for installation would help, especially for on-premise users."
"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."
"The ability to schedule scripts for the building and monitoring of jobs would be an advantage for this platform."
"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 18th in Data Science Platforms with 1 review 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 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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