[idjango]

You should read the link below [1]. Even if it's not uber scale I suspect yandex to use something similar.

I agree that python implementation of graphite was not particularly fast but there was faster implementation in C that companies used first to significantly increase performance. Then coordination of storage backend becomes complex when you try to scale the initial design. This is where clickhouse really shine. It provide out of the box distributed storage with compaction, rollup and fast querying. The other layers are stateless, which means that they'll scale with your computing ressources.

M3DB is roughly doing the same thing as clickhouse but clickhouse is much more advanced database that has proven records of running at petabyte scale without a sweat. For example they now have tiered storage which means that you can store recent event in nvme and rollup to standard HDD...

[1]https://medium.com/avitotech/metrics-storage-how-we-migrated...