Does Neki solve for this, and if so how? My understanding of CAP theorem is that this basically requires some compromises around availability, but I'm curious as to what that looks like in practice here.
The usual way to run it is that you partition your db based on something like a user, so that single user gets a consistent DB, but anything cross-shard may not be.
I know when I worked at Block, Cashapp was using Vitess and getting cross-shard DB writes down and functioning correctly was one of the major blockers to adoption. (though I just did tls management for vitess and didn't write any workloads on top of it, so my impression might be a bit off)
Selfish doubts aside, congrats to Planetscale on the launch!
The pitch is compelling. I wonder how many teams will be able to operate sharded database setups in production as a result of this.
For example: point 08 says "Assign different tables or workloads to different shard groups" and point 02 says "Split hot shards as workloads grow". How do those interact ? Can a single table be split across multiple shards ? If so don't you need 2pc to enforce primary key constraints ?
The intro pages just read as AI slop.
I am looking for interdimensional and interuniversal scale. Which of you trust fund babies has a startup which is working on this problem?