Compare cache-aside, read-through, write-through, and write-back
Reported in King European engineering loops. Caching patterns for system design and backend performance tuning.
Interview scenario
Often asked in King loops at European offices (London, Berlin, Amsterdam, Paris, Stockholm, Dublin, and remote EU). Prepare a clear spoken answer plus key trade-offs.
Model answer
Try answering aloud first
Cover trade-offs, structure, and a concrete example before revealing the baseline response.
How to frame this at King: Connect your answer to measurable impact, clarity of thought, and trade-offs the team cares about. Below is a strong baseline response you can adapt with your own project examples.
Cache-aside (lazy loading): App reads cache first; on miss, loads DB, populates cache. Writes update DB then invalidate cache. Simple and common; risk of stale reads if invalidation fails.
Read-through: Cache library loads from DB on miss—app always talks to cache layer. Centralizes loading logic.
Write-through: Writes go to cache and DB synchronously—consistent but higher write latency.
Write-back (write-behind): Writes hit cache first; async flush to DB—fast writes, risk of data loss on crash.
Discuss TTL, eviction (LRU/LFU), stampede protection (single-flight locking), and CDN vs application vs database buffer cache. Pick pattern based on read/write ratio and consistency requirements.
Discussion
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