If you have different work loads for your data the first approach is to use 
different CF's. You can make changes to the row / key cache to allocate more 
cache to the important things. The OS will take care of using the rest of the 
memory to cache the disk access.

In this case there is not much difference between multiple CF's and multiple 
keyspaces. 

If after tuning CF's you still see an issue (or you have really different 
workloads) the next step is to use different clusters. See this recent post 
from edward http://www.mail-archive.com/user@cassandra.apache.org/msg17576.html
 
Cheers

-----------------
Aaron Morton
Freelance Cassandra Developer
@aaronmorton
http://www.thelastpickle.com

On 1/10/2011, at 5:18 AM, Ramesh S wrote:

> Thank you Jonathan for your quick reply.
> The reason I asked the question is because I have noticed some companies have 
> used Cassandra to store data (which needs frequent read writes ) in-memory 
> and have used other databases for data which is less frequently read/updated.
> So this created my doubt in my design decision.
>  Also we have a major portion of data which need not be in-memory . Right now 
> we have a design where everything is in the same keyspace. 
> So is there a way where we can may be swap that data, which is less demanding 
> , to disk , by keeping in a different keyspace.
> 
> Thanks 
> regards
> Ramesh
> 
> 
> On Fri, Sep 30, 2011 at 10:30 AM, Jonathan Ellis <jbel...@gmail.com> wrote:
> Short answer: no.
> 
> Longer: What problems do you hope to avoid by adding this complexity?
> 
> On Fri, Sep 30, 2011 at 9:45 AM, Ramesh S <investt...@gmail.com> wrote:
> >
> >
> > I have some data that would be read/write might be once during the entire
> > session, like authentication info.
> > When designing database with Cassandra is it advisable to keep the data that
> > is not frequently read/written to the database else where ?
> >
> > Thank you
> > regards,
> > Ramesh
> 
> 
> 
> --
> Jonathan Ellis
> Project Chair, Apache Cassandra
> co-founder of DataStax, the source for professional Cassandra support
> http://www.datastax.com
> 

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