[jjirsa]

Why throw away something proven to run at massive scale, that you understand and trust for something that's new, has never been run at that scale, and you have no experience running? If you have a team of software engineers, and the latency problem is a software problem, fix the software problem.

When you already know Cassandra, and you already know RocksDB, and you already have an engineering team, it makes far more sense to combine the two things you know how to use at scale than to try to use some new thing NOBODY has run at scale.

[welder]

> some new thing NOBODY has run at scale

Outbrain uses ScyllaDB in production at scale across multiple data centers. Not sure if it's Instagram scale, but still enough to prove it's reliability and performance.

https://www.outbrain.com/techblog/2016/08/scylladb-poc-not-s...

[jjirsa]

7 hosts in that poc, that is not "at scale"

[manigandham]

Scylla can handle 10-100x the load of Cassandra on the same servers. Scale is more than just the number of hosts.

[cnlwsu]

Data density is a thing. If u putting 10tb on a c* host, switching to Scylla doesn’t fix the issues that putting 1pb of data on a host would involve (ie backing that up). Throughput of 100mb of data done in marketing benchmarks are rarely relevant.

[manigandham]

Ok, but that's a different issue and nobody is suggesting 1PB of data on a single node as a good idea. The comment was that "scale" is more than just a simple count of nodes. Even if you keep the data the same size, Scylla can handle it with much better performance which is a good enough reason for many to use it.

[welder]

Since that poc they're using Scylla on hundreds of machines... that's just an old post.