Daniel Lozano

7 Cache Eviction Strategies You Should Know: 1. 𝐋𝐞𝐚𝐬𝐭 𝐑𝐞𝐜𝐞𝐧𝐭𝐥𝐲 𝐔𝐬𝐞𝐝 (𝐋𝐑𝐔) - Removes the least recently accessed item first. - Works well when older data is less likely to be used again. - Example: Browser cache, in-memory caches like Redis. 2. 𝐋𝐞𝐚𝐬𝐭 𝐅𝐫𝐞𝐪𝐮𝐞𝐧𝐭𝐥𝐲 𝐔𝐬𝐞𝐝 (𝐋𝐅𝐔) - Evicts the least accessed items over time. - Prioritizes keeping frequently used items in cache. - Example: Machine learning inference caches, recommendation systems. 3. 𝐅𝐢𝐫𝐬𝐭 𝐈𝐧, 𝐅𝐢𝐫𝐬𝐭 𝐎𝐮𝐭 (𝐅𝐈𝐅𝐎) - Evicts the oldest stored item first, regardless of usage. - Simple to implement but may remove still-relevant data. - Example: Simple queue-based caching systems. 4. 𝐑𝐚𝐧𝐝𝐨𝐦 𝐑𝐞𝐩𝐥𝐚𝐜𝐞𝐦𝐞𝐧𝐭 (𝐑𝐑) - Randomly evicts an item when the cache is full. - Low overhead, but less predictable performance. - Example: Used in some network routers. 5. 𝐌𝐨𝐬𝐭 𝐑𝐞𝐜𝐞𝐧𝐭𝐥𝐲 𝐔𝐬𝐞𝐝 (𝐌𝐑𝐔) - Opposite of LRU – evicts the most recently accessed item first. - Useful when recent data becomes obsolete quickly. - Example: Video streaming buffers, certain financial applications. 6. 𝐓𝐢𝐦𝐞 𝐭𝐨 𝐋𝐢𝐯𝐞 (𝐓𝐓𝐋) - Items are evicted after a set time limit (expiry time). - Prevents stale data, useful in distributed systems. - Example: DNS caching, API response caching. 7. 𝐓𝐰𝐨-𝐓𝐢𝐞𝐫𝐞𝐝 𝐂𝐚𝐜𝐡𝐢𝐧𝐠 - Uses a fast in-memory cache (e.g., Redis) & a slower persistent cache (e.g., disk-based). - Optimizes speed & storage by balancing hot and cold data. - Example: CDN caching, hybrid cloud storage solutions. 💡 No single strategy is perfect—the right choice depends on: - Data access patterns (frequent reads? high writes?) - System constraints (memory, CPU, disk space) - Performance trade-offs (latency vs accuracy) ♻️ Repost to help others in your network.