just my 2 cents
the best answer is always from the real-world practices :)
RocksDB https://rocksdb.org/ is the implementation of "state store" in Kafka
Stream and it is an "embedded" kv store (which is diff than the distributed kv
store). The "state store" in Kafka Stream is also backed up by
Hello Gareth,
A common practice for rolling up aggregations with Kafka Streams is to do
the finest granularity at processor (5 days in your case), and to
coarse-grained rolling up upon query serving through the interactive query
API -- i.e. whenever a query is issued for a 30 day aggregate you do
Hi,
We have a requirement to calculate metrics on a huge number of keys (could
be hundreds of millions, perhaps billions of keys - attempting caching on
individual keys in many cases will have almost a 0% cache hit rate). Is
Kafka Streams with RocksDB and compacting topics the right tool for a
