What is the difference between Golang cache and database?

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Release: 2024-06-03 20:34:59
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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.

Golang 缓存与数据库之间的区别?

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’ssync.Mapandgithub.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 usingsync.Mapcaching:

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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