I am facing kind of an different angle on the distribution problem, was wondering what you may recommend for it. Description:

A SMALL set of data that is both read & write. Each server holds a FULL copy of the data (since its small). However must be distributed between MANY MANY servers. When one server updates its local copy, the update must be propagated to the others. “Eventual consistency” is good enough but should be seconds not hours. Nice to have: bindings to PHP, C/C++.

The catch – do not want to add a data layer (no NFS, no DB) but rather keep it all between the symmetric identical “many many servers”.

Any suggestions other than “roll your own” ?

But not entirely w/o good reason. For example, I've never heard of Caché (nor has it come up in any of the NoSQL conversations in the community I track until now) – the chances are that any startup will be able to hire someone w/ expertise in that system is probably pretty low. I ended up putting together a system in less time that it would have taken to schedule a sales call, much less go through the evaluation process (built and launched for client over the weekend). Certainly for less cost than the evaluation time as well. Not to mention the inevitable incremental costs for upgrades, additional licensing, and support that comes w/ enterprise software.

In fact, I can't think of any large internet companies that isn't based primarily on an open source infrastructure supplemented by their own code (MS is an exception, but not in terms of depending on 3rd party technology, just avoiding most of the open source stuff).

I think for most startups the risk/expense/agility curve is just isn't a good fit for most niche 3rd party software infrastructure.

(Oh, also, peeking at the docs Caché doesn't support language bindings for the languages that the startup used, so that's another strike.)