Redis VS Polly

Since 2008 I have been an official Debian Developer and even the Debian Project Leader from 2017—2019. I have submitted over 4,000 bugs to the project, been part of several core teams and have released over 250 security updates as well (as part of the Debian Long Term Support initiative). Today, I am the release manager of the Lintian static analysis tool but I also maintain a number of popular packages such as Redis, Django and Memcached.

I think that sums it up pretty well. The description of redis at https://redis.io/ is "Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker.". Without knowing anything about the application that you want to build, I personally wouldn't have good feeling to use Redis, that's defined as an "in-memory data structure" as the primary database for it - compared to a NoSQL database like MongoDB or a relational database like MySQL or PostgreSQL. I've been using Redis in projects as a cache (similar to memcached) besides the main database.

In-process caching may be implemented in a Node.js application through libraries, such as node-cache, memory-cache, api-cache, and others. There is a wide variety of distributed caching solutions, but the most popular ones are Redis and Memcached. They are both in-memory key-value stores and optimal for read-heavy workloads or compute-intensive workloads due to their use of memory rather than the slower on-disk storage mechanisms found in traditional database systems.

Redis stands for REmote DIctionary Server. It is an open source, fast NoSQL database written in ANSI C and optimized for speed. Redis is an in-memory database that means that all data in Redis is stored in RAM, delivering the fastest possible access times to the data for both read and write requests.

Here, have some cache

Redis is an in-memory key-value store which can save abstract data structures with high performance. The open-source software is typically used for database, messaging, and caching functions.

According to its GitHub repository, Redis (stands for REmote DIctionary Server) is an in-memory data structure store. It is a disk-persistent key-value database with support for multiple data structures such as strings, hashes, lists, sets, bitmaps, etc.

Redis offers highly performant and efficient read and write along with few operations mentioned in this article. There are lots more. For more information, you can visit the documentation.

If you need distributed access then redis

Can this done by Polly https://github.com/App-vNext/Polly

In C# there's a very good library called Polly (https://github.com/App-vNext/Polly). It's highly customizable and allows you to do a lot more than just circuit breaking (e.g. Retry policies). There's most likely a similar type of library for what language you use

That said... You might want to look up the polly library.

This exact logic is implemented in amazing Polly library, specifically it's Retry policy.

Maybe something like Polly?

Just for the sake of simplicity, I'll show you how to implement the Circuit Breaker pattern only on our API Gateway. If you want to dive deeper on the pattern and implement it between two services, you can head over to the Polly project on Github. Polly is the same library Ocelot uses to implement their Circuit Breaker. Now, let's get to the code!

One of my favorite is Polly which provides a simple Circuit Breaker implementation plus other resiliency tools.