Presentation: When Every Bit Counts: How Valkey Rebuilt Its Hashtable for Modern Hardware

Cache efficiency is no longer a nice-to-have optimization—it's becoming table stakes for data infrastructure. Valkey's move toward cache-aware hashtable designs reveals something we've been skirting around: traditional pointer-chasing data structures kill performance on modern CPUs regardless of algorithmic cleverness. For teams running Redis-compatible systems at scale, this matters immediately. If your in-memory stores are thrashing L3 caches, you're leaving 30-40% performance on the table while paying full price in hardware. The Swedish table approach forces us to rethink how we structure lookups and collisions, prioritizing memory locality over textbook elegance. Real impact: audit your hot-path data structures now. If you're building feature stores, real-time aggregation layers, or session caches, consider whether your implementation assumes idealized hardware or respects actual CPU topology. This isn't academic—it translates directly to reduced latency variance and lower operational costs in production.