Microsoft R Open / Revolution R Enterprise vs. NVIDIA RAPIDS

If you are a MS shop specifically, or have more generic data requirement needs from Microsoft sourced data this will work well. If you have a lot of disparate data across a number of unique platforms/cloud systems/3rd party hosted data warehouses then this product will have issues or a lack of documentation on the net. Performance-wise this product is equal to other R platforms out there.

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

• It allows distributed algorithm runs on Hadoop HDFS cluster
• It allows using different file formats such as SAS7BAT files or complex files in tab or comma delimited making data munging easier
• It provides scalable solutions by allowing users to re-use R scripts and distributing the computing over nodes through RHadoop

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

Incentivized

• Very steep learning curve... for such a quick and useful tool the learning curve is unacceptable.
• Very dangerous in the wrong hands. Because most add-ons are pre-written, you have to trust the community that malicious script is not used.

Incentivized

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

Incentivized

In general, Revolution Analytics brings a lot of value to the organization. The renewal decision would be based on return on investment in terms of quantified actionable insights that are getting generated against the cost of the product. Additionally, market brand of the tool and reputation risk in terms of possible acquisition and its impact to overall organizational analytic strategy would be considered as well.

It is good, easy to use, improvements are being made to the product and more info being shared in the community. It just needs some more time to become more integrated to other platforms and tools/data out there.

Incentivized

Generally support comes through the forums and user generated channels which are helpful, easy to access, quickly turned around and provided by knowledgeable users. However the support channels are not employees and the channels are often used as a way to learn quick difficult elements of R. Better design, users interface and tutorial options would alleviate the need for this sort of interaction.

Incentivized

The two are different products for different purposes. But for someone who has little or no experience in R programming, Power BI would be better for starting with. Having said that, Microsoft R is built on R, thus allowing for customization of complex calculations not typically available otherwise.

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

• Helped save company money versus buying other stat software

Incentivized

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

Incentivized