Cloudera Data Science Workbench vs. NVIDIA RAPIDS

Organizations which already implemented on-premise Hadoop based Cloudera Data Platform (CDH) for their Big Data warehouse architecture will definitely get more value from seamless integration of Cloudera Data Science Workbench (CDSW) with their existing CDH Platform. However, for organizations with hybrid (cloud and on-premise) data platform without prior implementation of CDH, implementing CDSW can be a challenge technically and financially.

Incentivized

NVIDIA RAPIDS drastically improves our productivity with near-interactive data science. And increases machine learning model accuracy by iterating on models faster and deploying them more frequently. It gives us the freedom to execute end-to-end data science and analytics pipelines.

Incentivized

• One single IDE (browser based application) that makes Scala, R, Python integrated under one tool
• For larger organizations/teams, it lets you be self reliant
• As it sits on your cluster, it has very easy access of all the data on the HDFS
• Linking with Github is a very good way to keep the code versions intact

Incentivized

• Visualization
• Deep learning pipeline
• State of the art libraries

Incentivized

• Installation is difficult.
• Upgrades are difficult.
• Licensing options are not flexible.

Incentivized

• Its not flexible and cost effective for all sizes of organizations.
• I appreciate it has hassle-free integration.

Incentivized

Cloudera Data Science Workbench has excellence online resources support such as documentation and examples. On top of that the enterprise license also comes with SLA on opening a ticket to Cloudera Services and support for complaint handling and troubleshooting by email or through a phone call. On top of that it also offers additional paid training services.

Incentivized

Both the tools have similar features and have made it pretty easy to install/deploy/use. Depending on your existing platform (Cloudera vs. Azure) you need to pick the Workbench. Another observation is that Cloudera has better support where you can get feedback on your questions pretty fast (unlike MS). As its a new product, I expect MS to be more efficient in handling customers questions.

Incentivized

RAPIDS GPU accelerates machine learning to make the entire data science and analytics workflows run faster, also helps build databases and machine learning applications effectively. It also allows faster model deployment and iterations to increase machine learning model accuracy. The great value of money.

Incentivized

• Paid off for demonstration purposes.

Incentivized

• Efficient way to complete tasks
• De-facto GPUs standard

Incentivized