Why Database Caching Strategies Break Under Write-Heavy Workloads

On this episode of Database Tech with Fexingo, Lucas and Luna dig into why caching — a go-to performance fix — can actually harm your database under write-heavy workloads. They break down the invalidation problem using a concrete example: a social media platform tracking daily active users. Lucas explains how a naive time-to-live cache can return stale data for hours, while Luna pushes back on the common 'just use Redis' mindset. They explore cache-aside, write-through, and write-back strategies, revealing why the latter introduces serious crash risks. The hosts also tie the discussion to real-world trade-offs at companies like Uber and Twitter, where read-heavy vs. write-heavy patterns demand totally different caching architectures. No ad break, no fluff — just a focused 10-minute conversation on one specific database design decision that can make or break application performance. #Database #Caching #WriteHeavyWorkloads #CacheInvalidation #CacheAside #WriteThrough #WriteBack #Redis #TimeToLive #DatabasePerformance #DataEngineering #TechPodcast #FexingoBusiness #BusinessPodcast #DatabaseTech #SQL #NoSQL #LucasAndLuna Keep every episode free: buymeacoffee.com/fexingo