[disgruntledphd2]

If I were running R in production, then I'd probably fit models on some kind of batch process and then serve up the predictions/output from a DB or something.

In general, R is not well-suited for DB-backed websites in real-time, but you can certainly use the outputs in production.

You can do it, but I'm not sure it's worth the effort. You could probably provide a predict() interface in real-time if it was reasonably quick.

[sandGorgon]

So I have seen a couple of large data science driven startups (like consumer finance) to throw R on 128gb machines and call it a day. That's reasonably going to be my plan except that I can't make it work very well.

I really wish pandas had a "save workspace" feature - R does that very well. No point in saving to dB if you're going to need the data set in memory anyway.... Or use Hadoop.