We (I'm a co-founder) run the following: - 1B (10^9) rows/sec with 86 servers https://www.scylladb.com/2019/12/12/how-scylla-scaled-to-one-billion-rows-a-s

We (I'm a co-founder) run the following: - 1B (10^9) rows/sec with 86 servers https://www.scylladb.com/2019/12/12/how-scylla-scaled-to-one-billion-rows-a-second/ https://www.scylladb.com/2019/12/12/how-scylla-scaled-to-one... - 1PB with 20 servers https://www.scylladb.com/presentations/operating-at-monstrous-new-scales-benchmarking-petabyte-workloads-on-scylladb/ https://www.scylladb.com/presentations/operating-at-monstrou... - Comcast moved from 970 Cassandra nodes (and 60 nodes of cache) to 78 Scylla nodes - https://www.scylladb.com/2020/01/15/comcast-sprinting-from-cassandra-to-scylla/ https://www.scylladb.com/2020/01/15/comcast-sprinting-from-c... - Palo Alto Networks run 8600 clusters(!) of ScyllaDB https://www.scylladb.com/2022/06/14/how-palo-alto-networks-replaced-kafka-with-scylladb-for-stream-processing/ https://www.scylladb.com/2022/06/14/how-palo-alto-networks-r... ScyllaDB excels in throughput and latency, we have also a better compaction algorithm that saves 37% of storage compared to C*. Usually one can replace lots of small nodes with gigantic nodes that have more resources and it allows much better management. To run 100PB Scylla will need more than 300 nodes, even thousands but definitely not what Apple throw at the problem.