In the discussed proposal datacenter failure is considered an extraordinary event with major performance implications, which is different than a global "write anywhere, read anywhere" multi-datacenter partitioned log model like Fauna.
FoundationDB has long supported both synchronous and asynchronous replication across regions, and its major users use multi-regional configurations. In the former mode, you will see 1xRTT latency for commits [1] from the active datacenter and 2xRTT latency for commits from other datacenters. In the latter mode, commits from the active datacenter are fast (0xRTT) but the durability property must be sacrificed if a region fails. I believe almost all users currently use asynchronous replication because the performance is so much better (than any geographically replicated synchronous database).
The new "satellite" replication model in FoundationDB 6.0 allows the best of both worlds: if you have two or more datacenters in each region (each storing transaction logs, but only one storing actual data) then you can do synchronous (0xRTT) commits to the regional datacenters and asynchronous replication to the other region(s). If there are failures in one region, the database can quickly and automatically fail over to the other region, while maintaining durability (by getting the last bits of transaction log from at least one datacenter in the failing region). Even if a whole region fails, as long as the failures of the datacenters and network links in it are spread out over time the database will complete a full ACID recovery. And in the worst case you can fall back to ACI recovery as in asynchronous replication.
The question you are linking to is asking about something different, the ability to have different parts of a single database have subgeographic latencies in different regions.
[1] You will also see 1xRTT latencies when you start transactions, but you can solve this by setting the causal_read_risky transaction option on all read/write transactions. This is not actually risky because if the reads in the transaction turn out not to be externally consistent, the transaction will not commit.
Very interesting. People really care about latency so we are also look at more datacenter-local journaling schemes that maintain consistency at the expense of a theoretically unlikely hit to durability.
What do you mean, "active datacenter"? Can all datacenters accept transactions concurrently?
If you are using Raft for replication, at any given time your replica set has a leader and it is located somewhere, and I would assume that writes from near there are faster than from anywhere else. In FoundationDB this is handled at a somewhat higher layer of the system, and since our transaction pipeline is (very roughly) resolve conflicts -> transaction log -> storage rather than transaction log -> resolve conflicts -> storage, we are also doing conflict resolution in that region.
Moreover, most current users of FoundationDB aren't willing to accept even 1xRTT latencies anywhere in their transaction lifecycle, so they can't abstract away which region is the fast one. A common way (though not the only way) to set things up is that your whole application (not just the database) is active in region A, but prepared to fail over at a moment's notice to run in region B. Ideally this comes at basically no performance penalty relative to a single-region setup in region A. Alternatively, it's possible to read or write the database from passive region(s) (and individual reads will normally happen from the local region with low latency), but each transaction has to pay a geographic latency at some point (or, in the case of read-only transactions, accept reduced consistency).
I think it would be possible to implement something analogous to satellite replication for Raft. It's a really nice set of tradeoffs for many applications, and if your cloud provider or equivalent has their act at all together instantaneous failures of all the datacenters in a region or their networking should really be pretty rare.
In the discussed proposal datacenter failure is considered an extraordinary event with major performance implications, which is different than a global "write anywhere, read anywhere" multi-datacenter partitioned log model like Fauna.