[kumarvvr]

I think it is more of an issue with not able to effectively model your data to suit the DDB paradigm.

DDB absolutely shines when you have to scale. I mean, have you ever tried setting up a cluster of SQL servers. It's a nightmare.

DDB is breezingly easy, as long as you know how to model your data effectively.

[hw]

Rdms is breezingly easy, as long as you know how to operate your clusters effectively

[fubbyy]

I could be wrong, but at truly large scale RDMS can’t compete, right? SQL simply can’t horizontally scale in the same way?

[oceanplexian]

Sure it can, and I’ve operated MySQL (Percona) at large scale for a social media company. You shard requests by user or something else, doesn’t matter if you have 50 DBs or 50,000. However in most cases you have to write the sharding mechanism yourself, and understand your workload and what such a system can and cannot do.

[fragmede]

Given perfect knowledge of access patterns, I bet you could. Especially since it's basically all reading and not writing. Horizontally scaled with many, many read-only replicas. But then there are lies, damn lies, and benchmarks. All the big companies running huge Oracle db installations are busy running their workloads, which probably don't look like Amazon Prime day traffic.

It's also impossible to have perfect knowledge of access patterns.

[dalyons]

even if you know how to do it, running large sharded rdbms clusters is incredibly far from "breezingly easy"