There's a pattern that's been quietly shipping in production for over a decade: take a large read-only dataset, compile it into a flat binary, and mmap it instead of deserializing it into Java objects. Lucene does it. Chronicle does it. LMDB does it. I built a reusable version of that pattern for rule/config/policy datasets and just open-sourced it. Repo: github.com/AlphaSudo/rimg The Problem You have a service that evaluates rules, policies, feature flags, or lookup tables on every request. The dataset is large (10K–1M+ entries), rarely changes, and lives on the heap as a big object graph. You're paying for it in: Heap pressure: Hundreds of MB of static data the GC has to scan every cycle. Startup time: Deserializing JSON or querying a DB to build the graph. Reload cost: Rebuilding the whole graph when the dataset updates. What rule-image does The .rimg format is a custom binary featuring: A CHD-style Minimal Perfect Hash (MPHF) index. Optional Bloom filter for fast negative lookups.…