Performance metrics usually assume predictable demand. Real systems rarely operate that way for long.
Access arrives unevenly. Some data is rarely touched, then suddenly needed. Other data is overused in ways never anticipated.
Walrus does not optimize for uniform demand. It accepts irregular access as normal. By avoiding tight coupling between access expectations and storage correctness, it reduces long-term surprises.
Predictability under uneven use matters more than efficiency under ideal conditions.