I don't see this brought up very often, but you have a huge world of flexibility in choosing growth rates beyond just adding constants for an O(n) amortized app

I don't see this brought up very often, but you have a huge world of flexibility in choosing growth rates beyond just adding constants for an O(n) amortized append time or multiplying by a constant for O(1). E.g., if you choose x -> x(1+1/log(x)) then you get an amortized append time of O(log(n)) while paying a memory overhead approaching 0% for large datasets. The distribution of (and SLOs for) appends relative to other operations can make that kind of idea more or less attractive, but even common data structures have a lot of room for improvement if you can tailor them to your use case a little bit.