Analyze cache performance by calculating hit ratio, miss ratio, effective access time, and speedup factor. Essential for optimizing caching strategies in web applications, databases, and CDNs.
Provide access times to calculate effective access time and speedup factor
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Cache hit ratio is the most critical metric for evaluating cache effectiveness. A high hit ratio means more requests are served from fast cache storage instead of slower backend systems. Our calculator helps you analyze current performance and identify optimization opportunities.
Cache hit ratio represents the percentage of requests successfully served from cache. When a request finds data in the cache (hit), it's served quickly. When data isn't in cache (miss), the system must fetch it from slower storage. Higher hit ratios mean better performance and lower backend load.
Cache Hit Ratio Formula
Hit Ratio = Cache Hits ÷ (Cache Hits + Cache Misses) × 100%Identify if your cache is effectively reducing latency. Low hit ratios indicate potential configuration or sizing issues.
Higher hit ratios reduce load on expensive backend systems like databases, APIs, and storage services.
Understand if your cache size is adequate or if you need to scale up to improve performance.
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Many applications have response time SLAs that depend on maintaining adequate cache performance.
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It depends on use case: CDNs typically target 85-95%, in-memory caches (Redis) often achieve 95%+, database query caches vary from 50-90%. Generally, above 80% is considered good for most applications.