I'm currently working on this. Speedup around 2x for most operations. Not kidding, quite a few startups are currently trying to optimize typical data operations with special algorithms.
You can find 'equivalents' to CPU data structures for FPGAs and speed up operations on/with them while still saving power. There's lots of trouble with how buffers are used and memory is accessed. So it's not a trivial task, but IF you can optimize generic data structures and replace the existing ones you basically have 2x the speed or half the energy consumption for any DB.
From the blog post:
> From here, I would be able to test my design, package it up as an Amazon FPGA Image (AFI), and then use it for my own applications or list it in AWS Marketplace.
As a user of those Marketplace images, you just look at the hourly fees. Your team needs to set this up, of course, and replace the old stuff, e.g. MongoDB with a new, sped-up FPGA-MongoDB. (And you'd need to fix some new bugs.)
If time is super-critical to you, e.g. if you're working with analytics: do you really need to speed up your processing pipeline? E.g. processing stuff not once but twice per day? If yes, then you'd better off having people on your team who understand all this and are able to fix and implement stuff themselves. Second scenario would be quite a bit more expensive, but still, FPGAs aren't rocket science and there's no way around them in the future.