Category
redis
8 articles across 4 sub-topics
System Design HLD Example: Real-Time Leaderboard
TLDR: Real-time leaderboards for 10M+ active users require an in-memory ranking engine. Redis Sorted Sets (ZSET) are the industry standard, providing $O(\log N)$ updates and rank lookups via an internal Skip List data structure. Relational databases ...
System Design HLD Example: Hotel Booking System (Airbnb)
TLDR: A robust hotel booking system must guarantee atomicity in inventory subtraction. The core trade-off is Consistency vs. Availability: we prioritize strong consistency for the booking path (PostgreSQL with Optimistic Locking) while allowing event...
System Design HLD Example: E-Commerce Platform (Amazon)
TLDR: A large-scale e-commerce platform separates catalog, cart, inventory, orders, and payments into independent microservices. The core architectural challenge is Inventory Correctness during flash sales—solved with a two-phase reservation pattern:...
System Design HLD Example: URL Shortener (TinyURL and Bitly)
TLDR: A URL shortener is a read-heavy system (100:1 ratio) that maps long URLs to short, unique aliases. The core scaling challenge is generating unique IDs without database contention—solved using a Range-Based ID Generator or a Distributed Counter ...
Redis Sorted Sets Explained: Skip Lists, Scores, and Real-World Use Cases
TLDR: Redis Sorted Sets (ZSETs) store unique members each paired with a floating-point score, kept in sorted order at all times. Internally they use a skip list for O(log N) range queries and a hash table for O(1) score lookup — giving you the best o...
System Design: Complete Guide to Caching — Patterns, Eviction, and Distributed Strategies
TLDR: Caching is the single highest-leverage performance tool in distributed systems. This guide covers every read/write pattern (Cache-Aside through Refresh-Ahead), every eviction policy (LRU through ARC), cache invalidation pitfalls, thundering her...
System Design HLD Example: Distributed Rate Limiter
TLDR: A distributed rate limiter protects APIs from abuse and "noisy neighbors" by enforcing request quotas across a cluster of servers. The core technical challenge is Atomic State Management—solved by using Redis Lua scripts to perform a "check-and...