You have to be careful here, as MongoDB and Cassandra use a different model of replication. Cassandra does not perform replication/synchronization on a per com

You have to be careful here, as MongoDB and Cassandra use a different model of replication. Cassandra does not perform replication/synchronization on a per command basis between the nodes. Roughly: the client writes to multiple nodes, which are mostly independent, so assuming client bandwidth is not the bottleneck, writing to W=2 nodes will not be much slower than W=1. In practice, since Cassandra's disk storage subsystem is also fast for writes, it's overall very fast at raw writes. (As in, fastest in my benchmarks.) The trade-off is that its replication model is eventual consistency, and reads are somewhat slowish. On the other hand, their model works well in a multi-datacenter environment (along with Riak). MongoDB uses an asynchronous replication model. What seems to happen if you specify W=2 is that the master doesn't ACK the write to the client until one of the slaves has copied it off the master. In my measurements W=2 ran at a fixed ~30 writes/sec on EC2, which means this mode may as well not be there. (This W=2 performance problem was also verified by customers looking at MongoDB.) If you look at my company's product, ScalienDB, it uses highly optimized synchronous replication model (Paxos) and a storage engine designed for that. It's actually faster running in W=3 mode than certain other NoSQLs in W=1 mode. My bet is that this is what enterprises are going to want if they're going to use a NoSQL as a primary-copy database. (Test for youself, all products are open-source, it'll cost you less than $20 on AWS.)