go-cache VS groupcache

Why I am creating this package? There is an already existing memory cache package which creates (One Janitor for One Cache) So I am running into issues where many go routines are running in our use cases causing the application to crash due to some memory leakage in the library itself or maybe multiple timers running at same time casuing the issue. Also this is a very popular github library but just doesn't fits when I am creating many cache instances. So thought about creating one package by myself.

I wrote a new library called VCache (https://github.com/microup/vcache). VCahce differs from go-cache (https://github.com/patrickmn/go-cache) by using a key of type "any" instead of a key of type "string". I compared the performance of both libraries on the main operations: Add, Get, and Delete.

https://github.com/patrickmn/go-cache is a well known one. My cache module is for it's fast full text search thus I recommend only using mine if u are using a pre-set cache.

github.com - patrickmn/go-cache

> when they went a year without a release.

Cause these libraries depend on other libraries that are probably extremely out of date at that point and have their own security vulnerabilities.

An example of a project that hasn't been dismissed as "abandoned", is https://github.com/patrickmn/go-cache because it explicitly doesnt have dependencies.

So yeah, if you have a semi-complex library, a year without a release is abandoned.

implementing runtime cache using map seems doable, i may just learn from github.com/patrickmn/go-cache but i dont understand what does it mean cache locally using text file. does it mean I have to:

Though pretty simple but have a look at https://github.com/patrickmn/go-cache

As shown in the title, DREAMEMO is a distributed cache with out-of-the-box, high-scalability, modular-design features.The groupcache implementation is referenced, and re-structured, specific module differentiation is as follows:

I remember one of the first real-world uses of Go being the groupcache package: https://github.com/golang/groupcache (to serve Chrome downloads, IIRC?)

> comes with a cache filling mechanism. Whereas memcached just says "Sorry, cache miss", often resulting in a thundering herd of database (or whatever) loads from an unbounded number of clients (which has resulted in several fun outages), groupcache coordinates cache fills such that only one load in one process of an entire replicated set of processes populates the cache, then multiplexes the loaded value to all callers.

I read that group cache (https://github.com/golang/groupcache) can be used to sync servers around a key.

I've not tried this myself, but I've seen it suggested to use groupcache (https://github.com/golang/groupcache) to sync your servers.

https://github.com/golang/groupcache is managing distributed caching that addresses thundering herd problem of memcache.

How it goes sometimes. Check out https://github.com/golang/groupcache and of course the AWS golang SDK.

There is also groupcache, written by the same author as memcached, but better.