Insert performance with Cassandra
You might consider Redis.  Its single-node throughput is supposed to be faster.  It's different from Cassandra though, so whether or not it's an appropriate option would depend on your use case.
sorry for my English in advance. 
I am a beginner with Cassandra and his data model. I am trying to insert one million rows in a cassandra database in local on one node. Each row has 10 columns and I insert those only in one column family.
With one thread, that operation took around 3 min. But I would like do the same operation with 2 millions rows, and keeping a good time. Then I tried with 2 threads to insert 2 millions rows, expecting a similar result around 3-4min. bUT i gor a result like 7min...twice the first result. As I check on differents forums, multithreading is recommended to improve performance.
That is why I am asking that question : is it useful to use multithreading to insert data in local node (client and server are in the same computer), in only one column family?
Some informations :
 - I use pycassa
 - I have separated commitlog repertory and data repertory on differents disks
 - I use batch insert for each thread
 - Consistency Level : ONE
 - Replicator factor : 1