A benchmark of Redis, Memcached, DragonflyDB, and Cashews using the same FastAPI workload reveals that Redis falls behind on latency, throughput, and memory efficiency, while DragonflyDB and Cashews offer superior performance and developer experience for Python caching.
Facing high memory overhead, operational complexity, and scaling limits of a large Redis cluster, we migrated to DragonflyDB using a three‑stage shadow, dual‑write, and cut‑over process, achieving up to 25‑fold throughput increase, 80% cost reduction, and simpler maintenance while preserving compatibility with existing Redis clients.
DragonflyDB, a Redis‑compatible high‑performance KV store, delivers up to 25× the throughput of Redis while using 15‑30% less memory, and can be integrated into Spring Boot projects with zero code changes, offering faster latency, better resource utilization, and seamless migration.
Dragonfly DB is a high‑performance, Memcached‑ and Redis‑compatible in‑memory database that reportedly delivers up to 25× Redis throughput, with a shared‑nothing, multithreaded architecture; this guide shows quick Docker deployment on Linux/macOS, client access methods, Spring cache integration, and key usage notes.
