The one use case where a DB backed queue will fail for sure is when the payload is large. For example, you queue a large JSON payload to be picked up by a worker and process it, then the DB writing overhead itself makes a background worker useless.
I've benchmarked Redis (Sidekiq), Postgres (using GoodJob) and SQLite (SolidQueue), Redis beats everything else for the above usecase.
SolidQueue backed by SQLite may be good when you are just passing around primary keys. I still wonder if you can have a lot of workers polling from the same database and update the queue with the job status. I've done something similar in the past using SQLite for some personal work and it is easy to hit the wall even with 10 or so workers.
Every time some production environment can be simplified, it is good news in my opinion. The ideal situation with Rails would be if there is a simple way to switch back to Redis, so that you can start simple, and as soon as you hit some fundamental issue with using SolidQueue (mostly scalability, I guess, in environments where the queue is truly stressed -- and you don't want to have a Postgres scalability problem because of your queue), you have a simple upgrade path. But I bet a lot of Rails apps don't have high volumes, and having to maintain two systems can be just more complexity.
the problem i see here is that we end up treating the background job/task processor as part of the production system (e.g. the server that responds to requests, in the case of a web application) instead of a separate standalone thing. rails doesn’t make this distinction clear enough. it’s okay to back your tasks processor with a pg database (e.g. river[0]) but, as you indirectly pointed out, it shouldn’t be the same as the production database. this is why redis was preferred anyways: it was a lightweight database for the task processor to store state, etc. there’s still great arguments in favor of this setup. from what i’ve seen so far, solidqueue doesn’t make this separation.
For people that does not think it scales. A similar implementation in Elixir is Oban. Their benchmark shows a million jobs per minute on a single node (and I am sure it could be increased further with more optimizations). I bet 99,99999% of apps have less than a million background jobs per minute.
Comparing Redis to SQL is kinda off topic. Sure you can replace the one with the other but then we are talking about completely different concepts aren't we?
When all we are talking about is "good enough" the bar is set at a whole different level.
Nice article, I'm just productionising a Rails 8 app and was wondering whether it was worth switching from SolidQueue (which has given me no stress in dev) to Redis ... maybe not.
For Node.js, my startup used to use [Graphile Worker](https://github.com/graphile/worker) which utilised the same "SKIP LOCKED" mechanism under the hood.
We ran into some serious issues in high throughput scenarios (~2k jobs/min currently, and ~5k job/min during peak hours) and switched to Redis+BullMQ and have never looked back ever since.
Our bottleneck was Postgres performance.
I wonder if SolidQueue runs into similar issues during high load, high throughput scenarios...
Interesting migration story! I've been using Redis for background jobs for years and it's been solid, but the operational overhead is real.
Curious about your experience with SolidQueue's reliability - have you run into any edge cases or issues with job retries/failures? Redis has been battle-tested for so long that switching always feels risky.
Would love to hear more about your production experience after a few months!
I've benchmarked Redis (Sidekiq), Postgres (using GoodJob) and SQLite (SolidQueue), Redis beats everything else for the above usecase.
SolidQueue backed by SQLite may be good when you are just passing around primary keys. I still wonder if you can have a lot of workers polling from the same database and update the queue with the job status. I've done something similar in the past using SQLite for some personal work and it is easy to hit the wall even with 10 or so workers.
[0]: https://riverqueue.com/
https://oban.pro/articles/one-million-jobs-a-minute-with-oba...
When all we are talking about is "good enough" the bar is set at a whole different level.
That being said, I regret that we have switched from good_job (https://github.com/bensheldon/good_job). The thing is - Basecamp is a MySQL shop and their policy is not to accept RDMS engine specific queries. You can see in their issues in Github that they try to stick "universal" SQL and are personally mostly concerned how it performs in MySQL(https://github.com/rails/solid_queue/issues/567#issuecomment... , https://github.com/rails/solid_queue/issues/508#issuecomment...). They also still have no support for batch jobs: https://github.com/rails/solid_queue/pull/142 .
https://nanovms.com/dev/tutorials/running-postgres-as-a-unik...
Turns out it is a matter of feature set.
We ran into some serious issues in high throughput scenarios (~2k jobs/min currently, and ~5k job/min during peak hours) and switched to Redis+BullMQ and have never looked back ever since. Our bottleneck was Postgres performance.
I wonder if SolidQueue runs into similar issues during high load, high throughput scenarios...
Curious about your experience with SolidQueue's reliability - have you run into any edge cases or issues with job retries/failures? Redis has been battle-tested for so long that switching always feels risky.
Would love to hear more about your production experience after a few months!