Oh... I just found this in the high scalability web site (http://highscalability.com/scaling-twitter-making-twitter-10...):

    Update 6: Some interesting changes from Twitter's Evan
    Weaver: everything in RAM now, database is a backup; peaks 
    at 300 tweets/second; every tweet followed by average 126 
    people; vector cache of tweet IDs; row cache; fragment 
    cache; page cache; keep separate caches; GC makes Ruby 
    optimization resistant so went with Scala; Thrift and HTTP 
    are used internally; 100s internal requests for every 
    external request; rewrote MQ but kept interface the same; 
    3 queues are used to load balance requests; extensive A/B 
    testing for backwards capability; switched to C memcached 
    client for speed; optimize critical path; faster to get the 
    cached results from the network memory than recompute them locally.