Options for deploying R models in production

Question

There doesn't seem to be too many options for deploying predictive models in production which is surprising given the explosion in Big Data.

I understand that the open-source PMML can be used to export models as an XML specification. This can then be used for in-database scoring/prediction. However, it seems that to make this work you need to use the PMML plugin by Zementis which means the solution is not truly open source. Is there an easier open way to map PMML to SQL for scoring?

Another option would be to use JSON instead of XML to output model predictions. But in this case, where would the R model sit? I'm assuming it would always need to be mapped to SQL...unless the R model could sit on the same server as the data and then run against that incoming data using an R script?

Any other options out there?

Answer 1

There are so many options available today, because of the current deployment trend of the cloud. 

You can check out these following options to deploy your R model:

• AWS

• openCPU

• AzureML

• DeployR

• yhat 

• Domino

• Sense.io

Hope this answer helps.

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