I've got serious "Key value fatigue." Inevitably these articles are always glowing but somewhere in the comments or on usenet you find the thread saying "we actually tried this and it fell on its face in production." I'm tired of articles that spend the whole time talking about features and showing single-machine "hello world"-esque 'performance tests' while neglecting the things people making IT decisions care about: does it actually work?<p>For us, we're using tokyo and it explodes at 70GB of data, though I'm guessing its a configuration issue or something. We purge it every week now since its just used as a persistent cache and I haven't looked into why, but it puzzles me how it can just basically break at a certain limit and not just start pushing things to disk.<p>To cut through the noise, can anyone here vouch for a simple "plug and play" kv store that actually works as advertised, at scale, and ideally is distributed so I can just add nodes as needed? Third party tall tales and anecdotes don't count, I want you to explain in detail your own personal experience running one of these things on a real, live, many-noded system. CouchDB, MongoDB, Tokyo, Redis, HBase, MemcacheDB, Voledmort, Cassandra, the list goes on (I realize not all of these are strict k-v stores), who out there other than the original authors can get up front and say these things work well?
MongoDB works very well for us with 100GB of data per collection, although we did run into a severe bug with .count not using an index, totally killing performance (we're talking 60 seconds to return).<p>Inserts and indices, however are very very fast, and the bug was fixed incredibly quickly and now works in trunk.<p>It doesn't seem quite cooked yet, but it's a very very nice start, and promises much. I prefer it to the other KV stores that are out there right now, anyway.