How many threads / processes do you have performing the writes? How big are the mutations ? Where are you measuring the latency ?
Look at the nodetool cfhistograms to see the time it takes for a single node to perform a write. Look at the nodetool proxyhistograms to see the end to end request latency from the coordinator. ^ the number on the left is microseconds for both. Generally cassandra does well with more clients. Cheers ----------------- Aaron Morton Freelance Cassandra Consultant New Zealand @aaronmorton http://www.thelastpickle.com On 17/04/2013, at 2:56 PM, Jabbar Azam <aja...@gmail.com> wrote: > MySQL cluster also has the index in ram. So with lots of rows the ram > becomes a limiting factor. > > That's what my colleague found and hence why were sticking with Cassandra. > > On 16 Apr 2013 21:05, "horschi" <hors...@gmail.com> wrote: > > > Ah, I see, that makes sense. Have you got a source for the storing of > hundreds of gigabytes? And does Cassandra not store anything in memory? > It stores bloom filters and index-samples in memory. But they are much > smaller than the actual data and they can be configured. > > > Yeah, my dataset is small at the moment - perhaps I should have chosen > something larger for the work I'm doing (University dissertation), however, > it is far too late to change now! > On paper mysql-cluster looks great. But in daily use its not as nice as > Cassandra (where you have machines dying, networks splitting, etc.). > > cheers, > Christian
