The retro names cross-region quorum as the root cause, and the arithmetic in the same post says quorum is only part of the bill. Staging measured P99 18ms on a single-Region cluster [12]. Mumbai-Singapore P99 network latency is given as 35ms [16]. Those two numbers sum to 53ms [2]. The reported production figure under load is 170 to 190ms [16], so the cross-region round trip explains roughly a fifth of the increase over staging [3]. The retro attributes the remainder to local processing under load [16].
My read of that gap is queueing, not network. Every write now holds its transaction state for one extra inter-Region round trip before it can commit [16]. At a fixed arrival rate, longer service time means more transactions in flight at once, and the local resource that was comfortable at 18ms is not comfortable at 53ms. That is why the first alert arrived at P99 95ms [14], which was already 1.9 times the 50ms contract [6], and why the peak figure landed at 3.6 times it [1]. The team filed the 95ms reading under cluster warm-up [14]. Warm-up is a remarkably durable diagnosis.
Treat the latency figures here as one practitioner's measurements rather than a spec, because the same author's three posts do not describe the same machine. One calls the commit protocol a set of Paxos variants tuned for geographic latency [7]. Another calls it a physical-clock timestamp protocol in the manner of Spanner's TrueTime, with an AWS implementation, giving serializable isolation across Regions [6]. Both accounts are dev.to posts under the same byline [21]. For either latency number to transfer to your system, your Region pair would need a comparable RTT, and your commits would need to be coordinated at the rate the retro observed, which was every single write [16].
What the primitive genuinely delivers is the failover step going away. One writable endpoint per peered Region sits behind a single logical database with nothing to provision [3], and if a Region drops, the survivor keeps serving reads and writes on the same logical endpoint [4]. Compare the Aurora Global Database path the team left: one to two minutes, a replica promotion that is semi-manual, and real data-loss exposure during high-write windows [5]. That is a real RTO and RPO improvement at the database.
It stops at the database. Serialization conflicts surface as aborts the client must retry, which is the local relational mechanism applied across Regions [8], so the retry and idempotency logic is application code, not a cluster setting. Authentication moves too: DSQL leads with IAM rather than password-based database users as the main entry point [17].
The last constraint is the one that picks your RTT for you. Stockholm and Spain exist to close GDPR residency gaps in the Nordics and Iberia, and Mumbai and Singapore sit under RBI and MAS localization rules [19]. Residency dictates which Region pair you can use. That pair fixes the round trip, and the round trip is the floor under your write SLO [10]. Note also that the single-Region tally is 20-plus against 16 for multi-Region [2], so at least four Regions where DSQL runs cannot host half of a peered pair [5].
