ristretto VS Redis

1. Unfortunately, ristretto has been showing hit ratio around 0 on almost all traces for a very long time now and the authors don't respond to this in any way. Vitess for example has already changed it to another cache. Here are two issues about it: https://github.com/dgraph-io/ristretto/issues/346 and https://github.com/dgraph-io/ristretto/issues/336. That is, ristretto shows such results even on its own benchmarks. You can see it just by running hit ratio benchmarks on a very simple zipf distribution from the ristretto repository: https://github.com/dgraph-io/ristretto/blob/main/stress_test.... On this test I got the following:

That's exactly how Userify[0] used to work. (when it was Python; now that it's a Go app, we do the caching in memory using Ristretto[1]).

0. https://userify.com (team ssh key management/sudo authz)

1. https://github.com/dgraph-io/ristretto

I also do some hit ratio benchmarks and Theine's results are much better than Ristretto. See results in README: https://github.com/Yiling-J/theine-go#hit-ratios

If you know Caffeine(Java)/Ristretto(Go)/Moka(Rust), you know what Theine is. Python deserves a good in-memory cache library.

Thanks for sharing. There are a lot of options for embedded in-memory caches: https://github.com/dgraph-io/ristretto https://awesome-go.com/caches/ Do you have any comparisons or details on how your project has a different approach?

I made Cacheme years ago, which support redis and synchronous API only. Then I switch to Go and found that there are some awesome cache projects in Go(ristretto, gocache...), I also made my own Cacheme go version: cacheme-go. After trying asyncio and type hint, I think it's time to rewrite my old Cacheme.

zcached is an in-memory key-value cache exposing a memcached ASCII protocol-compatible interface, built on pluggable cache engines like Ristretto and freecache [0].

It's not performance-competitive with memcached, especially at higher thread counts. That said, it achieves about 1.1M ops/s, but at significantly higher P99 and P999 latency (as measured by memtier). See [1] and [2] for benchmark results from my 7950x-based workstation.

Disclaimer: This is a hobby project created for fun while hacking over the holidays. zcached is not a commercial product and never will be. Don't use it in production; consider this a technology demo more than anything.

I don't expect the source code to build outside of my environment, but for those interested in playing with it, binary artifacts are available at [3]. Try `zcached --address tcp:localhost:11211`.

[0] https://github.com/dgraph-io/ristretto, https://github.com/coocood/freecache

While I never used dgraph, I do use badger and ristretto and am similarly in a bind over their long-term survival (moreso badger than ristretto)...

There are also different packages used as a wrapper on top of the Go map based on what your requirements are (storing a lot of data) https://github.com/allegro/bigcache or (need performance) https://github.com/dgraph-io/ristretto. For basic use-cases, the standard Go map should be enough. Just keep in mind whether you need concurrent access to your data structure, in which case you should guard your map with a mutex .

MemoryDB documentation has an example for a Java application with the Lettuce client. The process is similar for other languages, but you still need to implement it. So, let's learn how to do it for a Go application with the widely used go-redis client.

We have setup a redis cluster with 3 master, and 3 slave nodes using redis-go package (https://github.com/redis/go-redis).

For building the RESTful Point of Sale service API, I've considered and selected a combination of technologies that would work seamlessly together. For handling HTTP requests and responses, using the Gin HTTP web framework would make sense because I think it seems complete and popular among Go community too. To ensure data integrity and persistence, I'm using PostgreSQL database with pgx as the database driver, the reason I choose PostgreSQL because it is the most popular relational database to use in production and offers efficient Go integration. I'm also implementing caching using Redis with go-redis client library, which provides powerful in-memory data storage capabilities.

Following the completion of the series — Secure and performant full-stack authentication system using rust (actix-web) and sveltekit and Secure and performant full-stack authentication system using Python (Django) and SvelteKit — I felt I should keep the streak by building an equivalent system in PURE go with very minimal external dependencies. We won't use any fancy web framework apart from httprouter and other basic dependencies including a database driver (pq), and redis client. As usual, we'll be using SvelteKit at the front end, favouring JSDoc instead of TypeScript. The combination is ecstatic!

IDE: use whatever make you productive. I personally use vscode. VCS: git, as golang communities use github heavily as base for many libraries. AFAIK Linter: use staticcheck for linting as it looks like mostly used linting tool in go, supported by many also. In Vscode it will be recommended once you install go plugin. Libraries/Framework: actually the standard libraries already included many things you need, decent enough for your day-to-day development cycles(e.g. `net/http`). But here are things for extra: - Struct fields validator: validator - Http server lib: chi router , httprouter , fasthttp (for non standard http implementations, but fast) - Web Framework: echo , gin , fiber , beego , etc - Http client lib: most already covered by stdlib(net/http), so you rarely need extra lib for this, but if you really need some are: resty - CLI: cobra - Config: godotenv , viper - DB Drivers: sqlx , postgre , sqlite , mysql - nosql: redis , mongodb , elasticsearch - ORM: gorm , entgo , sqlc(codegen) - JS Transpiler: gopherjs - GUI: fyne - grpc: grpc - logging: zerolog - test: testify , gomock , dockertest - and many others you can find here

Asynq uses https://github.com/go-redis/redis in order to connect to Redis. Whenever you create a client using go-redis, the client internally manages a connection pool, so when you need to execute a command in Redis the client just retrieves a connection from the pool and uses it. After using it, the connection is released and it goes back to the pool (no need to say that the Redis client is thread-safe).

Caching component go-redis ristretto

First thing first, we will install Redis client for Golang