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I'm reading through the paper, and I'm curious if I understand the implications of key subspacing and value dependent chaining correctly - do all reads and writes for a given key get forced to a single node? I understand how the replication that's described allows for failover when the point-leader fails, but does it also allow for scaling writes and key lookups?

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Reads and writes for a given key always go to a single node. As you add more machines with the same workload, you are handling fewer keys per machine. The flip side is, if the number of keys per machine stays constant, more machines directly translates into the ability to handle more keys.

HyperDex scales linearly as you can see in our scalability graph.

I think you're missing the point of the question. I'm not asking how you scale in general, I'm asking whether your replication scheme is only for failover or if it contributes to your scaling story - i.e., if a given key goes hot, does everything have to run through the point leader, or can each replica take writes/serve requests? It sounds like the former, which is fine, just wanted to clarify.

It's the former. I'd rather not sacrifice our strong consistency by using replicas to serve GET requests.

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