Explain caching strategies (Redis, Memcached).

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Caching strategies with tools like Redis and Memcached are widely used to improve application performance, reduce latency, and decrease the load on databases or APIs. Caching stores frequently accessed data in memory so that requests can be served much faster compared to repeatedly querying a slower data source.

Redis

Redis is an in-memory data store that supports advanced data structures like strings, hashes, lists, sets, and sorted sets. It allows persistence, meaning data can be saved to disk and restored later, making it more than just a cache. Redis also supports replication, clustering, and pub/sub messaging, which adds flexibility in distributed systems.

Strategies with Redis:

• Write-through caching: Data is written to cache and database at the same time. Ensures consistency but adds write latency.

• Write-back caching: Data is written to cache first, then asynchronously to the database. Improves write performance but risks data loss on failure.

• Read-through caching: Cache automatically fetches from the database if data is missing. Simplifies logic for applications.

• Time-to-Live (TTL): Expiration times are set to remove stale data automatically.

Memcached

Memcached is a high-performance distributed caching system designed purely for key-value storage. It’s simple, lightweight, and often used for caching small chunks of data like query results, sessions, or rendered pages. Unlike Redis, it does not support complex data types or persistence.

Strategies with Memcached:

• Cache-aside (Lazy loading): Application checks the cache first; if data is missing, it fetches from the database and stores it in cache. Efficient, but initial requests may be slow.

• Expiration policies: Items are set with a TTL to ensure stale data is removed.

• Eviction policies: Least Recently Used (LRU) ensures the oldest unused items are evicted when memory is full.

Comparison

• Redis: Feature-rich, supports persistence and clustering, ideal for complex data and real-time analytics.

• Memcached: Simple, lightweight, fast for straightforward key-value caching.

👉 Together, both are vital in reducing database load, enhancing user experience, and enabling scalable architectures.

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