Hi Bela,

Thanks for your inputs.

Yes I agree with you, n/w bandwidth wise it may not be an issue.

However, I've not got your point on how data store can be issue w.r.t 
scalability. Let me explain the data model a bit more here. All together I've 
around 250x1000 such entities, which would be replicated across 20 nodes (in 
about 2-3 mins timeframe). Now each entity being a size of 1 KB, we have 
provisioned for 250MB memory at each instance level (that means every node has 
all the state of the system). Given that I think with increase in number of 
instances in the cluster, the memory need would not increase. Please let me 
know if you think otherwise. However, I agree increase in average data size 
would surely be a scalability issue.

My concern is more with the CPU cycles which will go in marshaling/unmarshaling 
data. Given that every instance would receive data from all other (N-1) 
instances, the CPU cycles in marshaling the data would grow in all nodes in 
addition of more nodes in the cluster. 

Also I'm not sure how it would impact the locking. Assuming that use of MVCC 
locking strategy would take care of this.

By the way, I'm interested to know when is the target date of release of 
consistent hash algorithm (CHA) based (select where keys reside) distributed 
caching mode (ISPN-30). That would surely solve the scalability problem what I 
see in this case.

Regards,
Sourav

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