Earlier quoted context omitted.
Nope your explanation made sense, thank you! When I wrote that I was wondering if it used a second 2N+1 dataset just for coordination & consensus. This has the benefit of separating data from consensus, allowing the N of N+1 data failure. But at the end of the day consistency still comes down to a N of 2N+1 failure tolerance of that second coordination state. It's smaller easier to replicate etc etc but it seems like…
You only have to write to the coordination state when there is a failure. You can commit millions of transactions in the happy case without ever doing such a write. And failure detector performance and other engineering concerns are usually more of a limitation, in practice, on the performance of recovery than the latency of the coordination state consensus, even when the coordinators are geographically distributed.
In the best case with no failures this works great. But as the number of failures increases, I feel like due to the extra synchronization there will be an inflection point where the cost of the extra layers of coordination will be higher than just synchronizing the data directly. But due to 'other concerns' that inflection point is pushed back by a lot.
Is that a reasonable characterization?