cache.md

Cache

Cache aside

Application is responsible for reading and writing to the DB (using write-through or write-back policy)

The cache doesn't interact with the storage directly

Cache aside vs. read-through

Cache aside:

• Data model can be different from DB

Read-through:

• Same data model as DB
• Can use the refresh-ahead pattern

Cache eviction policy

• LRU (Least Recently Used)
• LFU (Least Frequently Used)
• FIFO

Cache locations

• Client caching
• CDN
• In memory
• Distributed cache
• Database caching (query or object)

Cache: refresh-ahead

Cache to automatically refresh any recently accessed entry prior to its expiration

Used with read-through cache

• Pro: can result in reduced latency
• Con: not accurately predicting which items are likely to be needed in the future

Cache: write through vs. write back

Main difference: consistency

Write through:

1. Write to the cache and the DB in a single DB transaction (may still lead to cache inconsistency if the DB commit failed)
2. Return

Write back:

1. Write to the cache
2. Return
3. Asynchronously store in DB

Four main distributed cache benefits

• Improve read latency
• Can improve availability (e.g., DB unavailable, responses are served from the cache)
• Save computation time (e.g., SQL computation)
• Independently scalable from the rest of the system

Main metric for cache

Cache hit ratio: hits / total accesses

Read-through cache

Read-through cache sits in-line with the DB

Single entry point

When to use a cache

• Speed up reads
• Response complex to compute