Announcement
Ristretto - 高性能 Go 内存缓存
Ristretto is a high-performance, memory-bound, concurrent cache written in Go, designed for applications requiring efficient caching with strict memory limits.
Project Introduction
Summary
Ristretto is an open-source, high-throughput Go cache library optimized for memory efficiency and performance. It implements cutting-edge caching algorithms to deliver superior hit ratios compared to standard LRU or LFU caches.
Problem Solved
Traditional caches often struggle with efficiently managing memory and achieving high hit rates under heavy load, especially in concurrent environments. Ristretto addresses this by providing an advanced admission and eviction policy tailored for performance and memory control.
Core Features
Advanced Admission Policy
Based on the Cache with Optimal Replacement Policy (CORP) principles, offering near-optimal hit ratios.
Cost-Aware Eviction
Allows assigning costs to cache items, ensuring more valuable items are retained longer.
Thread-Safe and Concurrent
Designed for safe concurrent access from multiple goroutines without external locking.
Memory-Bound Operation
Strictly adheres to configured memory limits, making it suitable for memory-constrained environments.
Tech Stack
使用场景
Ristretto is well-suited for various applications needing a robust and memory-efficient cache:
Database Query Caching
Details
Caching database query results to avoid repeated database calls for frequently requested data.
User Value
Significantly reduces database load and improves application response times.
API Response / Computation Result Caching
Details
Storing results from external API calls or computational results that are expensive to recompute.
User Value
Decreases latency and external service dependencies, enhancing application resilience.
Microservice State Management
Details
Maintaining small, frequently accessed state or configuration data across multiple requests or processes within a microservice.
User Value
Provides fast access to shared data, avoiding bottlenecks and serialization overhead.
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