I also ran an exhaustive analysis and had similar conclusion. I found that TinyLFU (mentioned in the article) matches or beats LIRS in database and search workl

I also ran an exhaustive analysis and had similar conclusion. I found that TinyLFU (mentioned in the article) matches or beats LIRS in database and search workloads. It is also much simpler to implement and is more memory efficient. https://github.com/ben-manes/caffeine/wiki/Efficiency https://github.com/ben-manes/caffeine/wiki/Efficiency The W-TinyLFU variant better handles recency by using an admission window so that new entries are not immediately discard. This resolves antirez's concern and improves performance in sparse burst workloads. In a way its similar to the HIR/LIR regions (window/main) using TinyLFU as a frequency filter. Happy to work with you, antirez, and others to simulate more policies and add trace files.