In general consensus based systems are not good when latency and performance actually matter and in real world WAN setups, where connectivity issues are pretty much constant. These are fundamental limitations they can't fix.
Additionally, FaunaDB gives you the tools to work within a global environment with _safe tradeoffs_. For example, reads at SI/Serializable can be fast and uncoordinated. You choose per-query.
That said, I don't think it's reasonable to infer that because failures occur more often than we'd like, systems based on consensus are always inappropriate for latency and performance sensitive systems. While there are minimum bounds on latency in consensus systems, there are also plenty of human-scale problems for which that bound isn't a dealbreaker. Moreover, some types of computation (e.g. updates in sequentially consistent or snapshot isolated systems) simply can't be performed without paying the same costs as consensus. Consensus can be an appropriate, and in some cases the only possible solution, to some problems.
For example, a 7 replica FaunaDB cluster can lose 3 replicas and maintain availability for reads and writes; better than Aurora in your example.