bull VS Redis

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

Data Handling: Utilizes Windmill for data pipelines, with a primary database powered by PostgreSQL. Auxiliary data storage is handled by MongoDB, with Redis for caching to optimize performance

One of the challenges Redis labs here have is that there's very little reason for their userbase to stay loyal to them.

antirez retired from Redis development a few years ago.

From https://github.com/redis/redis/graphs/contributors it looks like activity since he left has been mostly from people who didn't overlap with him much.

Redis Labs have not shown themselves to be outstanding stewards of the project as far as I can tell. Why shouldn't people support the fork?

Redis

Redis - real time data storage with different data structures in a cache

[0] https://github.com/redis/redis/blob/unstable/CONTRIBUTING.md

Cache: a Redis cache