RP has extremely good performance and scalability properties. Many uses of RP in the Linux Kernel have resulted in several orders of magnitude performance improvement compared to locking and transactional memory. Is it easy to program with? RP is not difficult to program with. Allowing each execution sequence to proceed using its own view of memory, by default, simplifies concurrent programming because it prevents memory from changing spontaneously. Threads are guaranteed to observe coherent memory, i.e., memory will contain values that were actually written at some time in the past. Read paths also exhibit deterministic performance characteristics, since they can not block or retry. This feature simplifies programming of time-sensitive systems. Nevertheless, RP is a new programming paradigm with a new interface and there are several ways to misuse it. Read Copy Update (RCU), an early example of RP, has seen extensive use in the Linux Kernel at over 2000 uses
James Hamilton has published a thorough summary of Facebook's Cassandra, another scalable key-value store for your perusal. It's open source and is described as a "BigTable data model running on a Dynamo-like infrastructure." Cassandra is used in Facebook as an email search system containing 25TB and over 100m mailboxes. # Google Code for Cassandra - A Structured Storage System on a P2P Network # SIGMOD 2008 Presentation. # Video Presentation at Facebook # Facebook Engineering Blog for Cassandra # Anti-RDBMS: A list of distributed key-value stores # Facebook Cassandra Architecture and Design by James Hamilton