Hi Cassandra developers, This is Dikang from Instagram, I'd like to share you some experiment results we did recently, to use RocksDB as Cassandra's storage engine. In the experiment, I built a prototype to integrate Cassandra 3.0.12 and RocksDB on single column (key-value) use case, shadowed one of our production use case, and saw about 4-6X P99 read latency drop during peak time, compared to 3.0.12. Also, the P99 latency became more predictable as well.
Here is detailed note with more metrics: https://docs.google.com/document/d/1Ztqcu8Jzh4USKoWBgDJQw82DBurQm sV-PmfiJYvu_Dc/edit?usp=sharing Please take a look and let me know your thoughts. I think the biggest latency win comes from we get rid of most Java garbages created by current read/write path and compactions, which reduces the JVM overhead and makes the latency to be more predictable. We are very excited about the potential performance gain. As the next step, I propose to make the Cassandra storage engine to be pluggable (like Mysql and MongoDB), and we are very interested in providing RocksDB as one storage option with more predictable performance, together with community. Thanks. -- Dikang
