Hi,
Currently we have an aggregation system (without kafka) where events are 
aggregated into Cassandra tables holding aggregate results.
We are considering moving to a KafkaStreams solution with exactly-once 
processing but in this case it seems that all the aggregation tables (reaching 
TB) need to be kept also in Kafka as ktables(Rocksdb)+compacted topics(Kafka) 
and the direction of computation would be: events topic -> KS aggregation -> 
aggregated topics -> one way sync to Cassandra using connector.
This poses two problems:
- the doubling on the total storage required for the system (which mainly 
stores aggregates), from 3 C* replicas to 2-3 K replicas + Rocksdb
- the time to reconstruct a Rocksdb instance during rollover update can be half 
an hour if the rollover is fast

Is there any way in Kafka Streams (even dropping the exactly once) in which we 
can work just with aggregate tables in Cassandra? For sure there is a way 
working with Kafka Consumer, pulling a batch of messages, aggregating, and 
adding aggregate to Cassandra. Not sure if possible with KafkaStreams given the 
higher level / FP modeling with its own clear advantages but this disadvantage.
Please advise,
Nicu Marasoiu
Geschäftsanschrift/Business address: METRO SYSTEMS GmbH, Metro-Straße 12, 40235 
Düsseldorf, Germany
Aufsichtsrat/Supervisory Board: Heiko Hutmacher (Vorsitzender/ Chairman)
Geschäftsführung/Management Board: Dr. Dirk Toepfer (Vorsitzender/CEO), Wim van 
Herwijnen
Sitz Düsseldorf, Amtsgericht Düsseldorf, HRB 18232/Registered Office 
Düsseldorf, Commercial Register of the Düsseldorf Local Court, HRB 18232

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