rsmq VS bull

All Credit for the original implementation of RSMQ goes to https://github.com/smrchy/rsmq :)

I was going through Redis Message Queue implementation in Node JS where I stumbked upon rsmq-worker module. While creating an instance of RSMQWorker in the rsmq-package, there's an option called "maxReceiveCount". Could someone whar this means? I read the description and it says "Receive count until a message will be exceeded"

To implement the solution with a queue, I used a package called 'Bull' (https://github.com/OptimalBits/bull). It's a library that helps with distributed job control, providing some very useful solutions for this type of work, such as background job processing, queues with priorities (FIFO, LIFO, and others), among other features. 'Bull' uses Redis for queue storage, so if your application crashes for any reason, once it's back online, it will continue executing the processes that are in the queue. In our case, we'll use the FIFO (First in, first out) queue solution, meaning priority based on arrival order.

We use bull-js for our distributed queue and event-driven library.

I'm using the excellent Redis based Bull.js as a job queue on Kubernetes.

For Job Queue, NestJs provides a package named @nestjs/bull as an abstraction/wrapper on top of Bull, a popular, well-supported, high-performance Node. js-based Queue system implementation.

I'm working on a large ETL project that involves handling queues for file integration. Currently, we are using Redis with Bull (https://www.npmjs.com/package/bull) for this purpose. However, to streamline our architecture and address security concerns, we are considering migrating the queue to PostgreSQL.

BullMQ is a pretty solid choice: https://github.com/taskforcesh/bullmq It's the successor of Bull: https://github.com/OptimalBits/bull

For Node specifically, things like Streams, understanding the asynchronous model completely, and the event loop. Also, queues tend to get used a lot in Node, so understanding the basic concepts behind that and how to use something like bull would be useful.

To do this properly, you need to put the task into queue, so if there are 1000 simultaneous uploads it won't kill your server but will be processed one by one. For the queue, see bull. Image hostings like AWS have some functionality for processing on their side, as an option.

This is a memory intensive process though and Heroku is OOM'ing with R14 errors. For this they recommend migrating intensive work like this to a Background Job via Redis, implemented in Bull and Throng