Redis VS celery

Database reads are expensive and slow. There's a multitude of other reasons why caching is essential, but for the project I'm working on I'm using supabase and their free tier supports only a limited amount of bandwidth. To avoid any rate-limiting I added a Redis layer in front of it to reduce the number of queries that hit the database directly.

The AWS Lambda function had been written in Java and therefore the team looked at different Java-based Redis drivers and eventually decided to use Jedis, a Java client for Redis designed for performance and ease of use. One of the reasons they chose to use Jedis was that it proved to be a lightweight library. Instantiating the client connection takes somewhere between 200-600ms (depending on the lambda memory settings) which impacts the cold start of the lambda function.

Caching - while it's not possible to cache everything, there's always a large percentage of your website / app that can be cached for an hour or ten minutes or 1 day etc... - all depends on the type of content but the longer you can cache for without negatively effecting content quality - the better. A good caching server example would be redis : https://redis.io/ or https://memcached.org/

The code uses the codehooks-js library to handle routing and middleware for the API, and the node-fetch library to make HTTP requests to the OpenAI API. The code also uses the built-in codehooks.io Key-Value store to cache the response from the OpenAI API for 60 seconds, in order to reduce the number of requests made to the OpenAI API (If you want to create your own Node.js Express backend, you just need to replace this cache with Redis for example).

Redis is an in-memory database and an open-source streaming engine with an IMDB data structure server that supports multiple data sets and data streams. This open-source platform has high throughputs and lower bandwidth due to its in-memory features that lead to faster processing of big data in data science applications.

Quirrel is a popular open-source webhook framework that makes it easy to add webhook support to your app. It makes uses of redis under the hood.

Redis

Redis is an in-memory data store that you can use as a database – or a cache in front of your regular database. The speed of Redis makes it ideal to cache database queries, complex computations, API calls, and session state.

I didn't finish college and I didn't see anything about Databases when I was there, so I don't have any theoretical background and on these 4 years coding at enterprise level my focus was totally in things like: Clean Code, SOLID, Design Patterns and other stuff code related and my only Database knowledge was about SQL/MySQL and Cache/Redis.

For the course I started to collect Open Source projects developed by corporations. There are a few where the product is open source such as Redis and Elastic. There are others where the company shares some of its code as open source such as Netflix, Facebook, or Booking.com.

I spent 3 years building a high scale crawler on top of Celery.

I can't recommend it. We found many bugs in the more advanced features of Celery (like Canvas) we also ran into some really weird issues like tasks getting duplicated for no reason [1].

The most concerning problem is that the project was abandoned. The original creator is not working on it anymore and all issues that we raised were ignored. We had to fork the project and apply our own fixes to it. This was 4 years ago so maybe things improved since them.

Celery is also extremely complex.

I would recommend https://dramatiq.io/ instead.

[1]: https://github.com/celery/celery/issues/4426

You can use celery to process the file for extraction, saving and creating rar/zip.

Celery not usefull for long term future tasks (far future) · Issue #4522 · celery/celery (github.com)

A different approach would be to have a main web application which would communicate with worker processes for time intensive operations as you describe. The web app would communicate with workers via some form of MQ or even database. Many solutions exists for that in different languages, one such solution is [Celery](https://github.com/celery/celery) primarily developed for Python but these days it also supports Node, Go, PHP and Rust.

Django-q2 only requires one dependency (except for Django itself). Celery, requires quite a few: https://github.com/celery/celery/blob/master/requirements/default.txt

Add a Celery + SQS setup for local development.

Celery -> What I'm currently considering using

same! the issue has been open with a lot of people experiencing it, but no resolution https://github.com/celery/celery/issues/4185

It seems to be a preliminary home for the docs while the issues with the current domain are sorted out (see issue #7351).

Several years ago, finishing another such task at work and spending a lot of time integrating the Pytest with SQLAlchemy (I am loving TDD so much), I decided to create a boilerplate for such a service. At that time, I used Celery. So I stuffed my project with Celery, SQLAlchemy, Docker and Pytest.