We performed a comparison between Cloudera Data Science Workbench and Databricks based on real PeerSpot user reviews.
Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."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."
"Databricks is a scalable solution. It is the largest advantage of the solution."
"The initial setup is pretty easy."
"Databricks gives you the flexibility of using several programming languages independently or in combination to build models."
"Databricks gives us the ability to build a lakehouse framework and do everything implicit to this type of database structure. We also like the ability to stream events. Databricks covers a broad spectrum, from reporting and machine learning to streaming events. It's important for us to have all these features in one platform."
"The most valuable feature of Databricks is the notebook, data factory, and ease of use."
"Databricks covers end-to-end data analytics workflow in one platform, this is the best feature of the solution."
"It is fast, it's scalable, and it does the job it needs to do."
"The technical support is good."
"Running this solution requires a minimum of 12GB to 16GB of RAM."
"The tool's MLOps is not good. It's pricing also needs to improve."
"Implementation of Databricks is still very code heavy."
"Databricks would benefit from enhanced metrics and tighter integration with Azure's diagnostics."
"Would be helpful to have additional licensing options."
"The integration and query capabilities can be improved."
"Pricing is one of the things that could be improved."
"Costs can quickly add up if you don't plan for it."
"Databricks can improve by making the documentation better."
"There are no direct connectors — they are very limited."
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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, Google Cloud Datalab and Alteryx, whereas Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku, Dremio and Microsoft Azure Machine Learning Studio. See our Cloudera Data Science Workbench vs. Databricks report.
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