What is the difference between Golang cache and database?

The difference between cache and database in Golang is: Data persistence: cache stores data temporarily, while database stores data persistently. Hit rate optimization: The higher the cache hit rate, the better the performance. Invalidation policy: Cache entries are expired based on TTL or LRU algorithm. Query flexibility: The database allows complex queries to be executed, with limited caching flexibility. Consistency: The database guarantees data consistency, but the cache does not.

The difference between cache and database in Golang

In Golang applications, cache and database are usually used to store temporary and persistent storage respectively sexual data. Understanding the difference between the two is critical to optimizing application performance.

Cache

• Temporary Storage: The cache stores recently accessed data items for quick retrieval.
• Hit rate: When data is obtained from the cache, it is called a hit. The higher the hit rate, the better the performance.
• Expiration policy: Cache entries are expired with a specified time to expiration (TTL) value or based on the least recently used (LRU) algorithm.
• Examples: Go’s sync.Map and github.com/go-cache/cache.

Database

• Persistent storage: The database stores data persistently, even if the application is restarted or the server is shut down, the data is retained Will keep it.
• Reliability: The database follows transactional semantics to ensure data integrity and consistency.
• Query flexibility: The database allows you to perform complex queries to filter, sort and retrieve data.
• Examples: SQL (such as MySQL), NoSQL (such as MongoDB).

Compare

Features	Cache	Database
Data persistence	Temporary	Persistence
Hit rate	Optimization	Not applicable
Invalidation strategy	Yes	No
Query flexibility	Limited	High
Consistency	Not guaranteed	Guaranteed

Practical Case

Suppose there is an e-commerce application that frequently accesses product price information. Storing this information in cache can greatly improve the loading speed of product pages. Here is sample code using sync.Map caching:

package main

import (
    "sync"
)

type Product struct {
    ID    int
    Price float64
}

var cache sync.Map

func main() {
    // 假设产品价格已从数据库加载
    products := map[int]*Product{
        1: &Product{ID: 1, Price: 100.00},
        2: &Product{ID: 2, Price: 200.00},
    }

    // 将产品价格加载到缓存中
    for _, product := range products {
        cache.Store(product.ID, product.Price)
    }

    // 从缓存中获取产品价格
    price, found := cache.Load(1)
    if found {
        fmt.Println("产品 1 的价格：", price)
    }
}

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