Databases

Introduction Every software system—whether it’s a relational database, a distributed key‑value store, an operating system, or a simple file server—must contend with the possibility of unexpected failure. Power outages, hardware faults, kernel panics, and bugs can all cause a crash that abruptly terminates execution. When a crash occurs, the system’s state may be partially updated, leaving data structures inconsistent and potentially corrupting user data. Crash recovery is the discipline of detecting that a crash has happened, determining which operations were safely completed, and restoring the system to a correct state without losing committed work. In the era of cloud-native services and always‑on applications, robust crash recovery is not a luxury—it’s a baseline requirement for high availability and data integrity. ...

Introduction Redis has been the de facto standard for in-memory data structures for over a decade, powering low-latency caching, ephemeral data, and real-time features. In recent years, Dragonfly emerged as a modern, Redis-compatible in-memory store that promises higher throughput, lower tail latencies, and significantly better memory efficiency on today’s multi-core machines. If you’re evaluating Dragonfly vs Redis for new projects or considering switching an existing workload, this article offers a comprehensive, practical comparison based on architecture, features, performance, durability, operational models, licensing, and migration paths. It’s written for engineers and architects who want to make an informed, low-risk choice. ...