neoq VS Ruby on Rails

I just want to commend OP - if they’re here - for choosing an int64 for job IDs, and MD5 for hashing the payload in Neoq, the job library linked [0] from the article.

Especially given the emphasis on YAGNI, you don’t need a UUID primary key, and all of its problems they bring for B+trees (that thing RDBMS is built on), nor do you need the collision resistance of SHA256 - the odds of you creating a dupe job hash with MD5 are vanishingly small.

As to the actual topic, it’s fine IFF you carefully monitor for accumulating dead tuples, and adjust auto-vacuum for that table as necessary. While not something you’d run into at the start, at a modest scale you may start to see issues. May. You may also opt to switch to Redis or something else before that point anyway.

[0]: https://github.com/acaloiaro/neoq

Neoq (https://github.com/acaloiaro/neoq) is a background job processor for Go.

Yes, another one. It began from my desire to have a robust Postgres-backed job processor. What I quickly realized was that the interface in front of the queue was what was really important. This allowed me to add both in-memory and Redis (provided by asynq) backends behind the same interface. Which allows dependent projects to switch between different backends in different settings/durable requirements. E.g. in-memory for testing/development, postgres when you're not running Google-scale jobs, and Redis for all the obvious use cases for a Redis-backed queue.

This allows me to swap out job queue backends without changing a line of job processor code.

I'm familiar with the theory that one shouldn't implement queues on Postgres, and to a large extent, I disagree with those theories. I'm confident you can point out a scenario in which one shouldn't, and I contend that those scenarios are the exception rather than the rule.

I created a background processor called Neoq (https://github.com/acaloiaro/neoq) that is likely to interest you.

This is exactly the thesis behind neoq: https://github.com/acaloiaro/neoq

Industry adoption - Without including the adoption of other popular and more established frameworks like Python, React, C#, and others, if we consider the adoption of Ruby frameworks, Rails easily eclipses Hanami. The Rails homepage lists some big-name organizations using the framework. On the other hand, as the new kid on the block, Hanami is not so widely adopted. We'll have to wait and see whether that will change in the future.

on April 23, 2024, a PR #51640 was merged into main branch of Ruby On Rails. This PR title is Use Module#include rather than prepend for faster method lookup.

[0] is a my favorite demonstration of it.

[0]: https://github.com/rails/rails/commit/b83965785db1eec019edf1...

Here's a real life example: Imagine a Ruby on Rails app on which a team of developers are working. The code is hosted on GitLab and all the work is coordinated using GitLab issues. In other words: For every commit, there's an associated issue and the issue number acts as a sort of primary key for documentation, time reporting and so forth. This convention has a few advantages, most notably the ability to easily learn more about how, when and by whom features were implemented as well as how this implementation came to be.

Ruby on Rails is regarded as one of the best ruby frameworks. It was the primary language in developing big projects such as Twitter and helped the language boost the community. Often referred to as “Rails,” Ruby on Rails is a web development framework with an MVC control structure and currently running its 6.1 version. The 16-year-old language has dramatically influenced the web development structures and managing databases, web pages, and other components on a web application.

In Rails 7.1, a new option _instance_methods is introduced, allowing developers to opt-out of the automatic generation of instance methods for enums. When enum is defined with _instance_methods: false, Rails will no longer generate methods like pending?, processed?, etc.

Rails isn't super opinionated about database writes, its mostly left up to developers to discover that for relational DBs you do not want to be doing a bunch of small writes all at once.

That said it specifically has tools to address this that started appearing a few years ago https://github.com/rails/rails/pull/35077

The way my team handles it is to stick Kafka in between whats generating the records (for us, a bunch of web scraping workers) and and a consumer that pulls off the Kafka queue and runs an insert when its internal buffer reaches around 50k rows.

Rails is also looking to add some more direct background type work with https://github.com/basecamp/solid_queue but this is still very new - most larger Rails shops are going to be running a second system and a gem called Sidekiq that pulls jobs out of Redis.

I'm looking forward to see what extractions from this will land on rails. For example: https://github.com/rails/rails/issues/50454

Here is what strict_loading does (source):

Kamal is a wonderfully simple way to deploy your applications anywhere. It will also be included by default in Rails 8. Kamal is trivial, but I don’t recommend using it on your development machine.