We performed a comparison between Cloudera Data Science Workbench and Databricks based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."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."
"We are completely satisfied with the ease of connecting to different sources of data or pocket files in the search"
"This solution offers a lake house data concept that we have found exciting. We are able to have a large amount of data in a data lake and can manage all relational activities."
"The solution is easy to use and has a quick start-up time due to being on the cloud."
"The initial setup is pretty easy."
"Databricks provides a consistent interface for data engineers to work with data in a consistent language on a single integrated platform for ingesting, processing, and serving data to the end user."
"The Delta Lake data type has been the most useful part of this solution. Delta Lake is an opensource data type and it was implemented and invented by Databricks."
"The time travel feature is the solution's most valuable aspect."
"Automation with Databricks is very easy when using the API."
"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."
"A lot of people are required to manage this solution."
"Databricks can improve by making the documentation better."
"I believe that this product could be improved by becoming more user-friendly."
"There should be better integration with other platforms."
"There are no direct connectors — they are very limited."
"Databricks' performance when serving the data to an analytics tool isn't as good as Snowflake's."
"The product needs samples and templates to help invite users to see results and understand what the product can do."
"The solution could improve by providing better automation capabilities. For example, working together with more of a DevOps approach, such as continuous integration."
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Cloudera Data Science Workbench is ranked 18th in Data Science Platforms with 2 reviews while Databricks is ranked 1st in Data Science Platforms with 78 reviews. Cloudera Data Science Workbench is rated 7.0, while Databricks 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 Databricks writes "A nice interface with good features for turning off clusters to save on computing". Cloudera Data Science Workbench is most compared with Amazon SageMaker, Microsoft Azure Machine Learning Studio, Dataiku Data Science Studio, Google Cloud Datalab and Alteryx, whereas Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku Data Science Studio, Microsoft Azure Machine Learning Studio and Dremio.
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