For an example, it handles stripe webhooks when users change their pricing tier - if you drop that message, users would be paying for something they wouldn't receive.
What do you say to those who don't want Google to know their usage info?
And if your needs are simpler like in this case then there are dozens of smaller pub/sub/queue systems that you could compare this to.
Kafka does more for streaming data, but doesn't do squat for relational data. You always need a database, but you sometimes can get by without a queuing system.
I've personally written real-time back-of-house order-tracking with rails and postgres pubsub (no redis!), and wrote a record synchronization queuing system with a table and some clever lock semantics that has been running in production for several years now -- which marketing relies upon as it oversees 10+ figures of yearly topline revenue.
Neither of those projects were FAANG scale, but they work fine for what is needed and scale relatively cleanly with postgres itself.
Besides, in a lot of environments corporate will only approve the use of certain tools. And if you already have one approved that does the job, then why not?
Most senior+ engineers that I know would hear that and recoil. Getting "clever" with concurrency handling in your home-rolled queuing system is not something that coworkers, especially more senior coworkers, will appreciate inheriting, adapting, and maintaining. Believe me.
I get that you're trying to flex some cool thing that you built, but it doesn't really have any bearing on the concept of "most cases" because it's an anecdote. Queuing systems are a thing for a reason, and in most cases, using them makes more sense than writing your own.
I am both a "senior+ engineer" that has inherited such systems and an author of such systems. I think you're overreacting.
Concurrency Control (i.e., "lock semantics") exists for a reason: correctness. Using it for its designed purpose is not horror. Yes, like any tool, you need to use it correctly. But you don't just throw away correctness because you don't want to learn how to use the right tool properly.
I have inherited poorly designed concurrency systems (in the database); yes, I recoiled in horror and did not appreciate it. So you know what I did? I fixed the design, and documented it to show others how to do it correctly.
I have also inherited OOB "Queuing Systems" that could not possibly be correct because they weren't integrated into the DB's built-in and already-used correctness system: Transactions and Concurrency Control. Those were always more horrific than poorly-implemeneted in-DB solutions. Integrating two disparate stores is always more trouble than just fixing one single source.
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> I get that you're trying to flex some cool thing that you built, but it doesn't really have any bearing on the concept of "most cases" because it's an anecdote. Queuing systems are a thing for a reason, and in most cases, using them makes more sense than writing your own.
I get that you're trying to flex that you use turnkey Queueing Systems, but it doesn't really have any bearing on the concept of "most cases", because all you've presented are assertions without backing. Queuing systems are good, for a specific kind of job, but when you need relational logic you better use one that supports it. And despite what MongoDB and the NoSQL crowd has been screaming hoarsely for the past decade, in most cases, you have relational logic.
But seriously though, postgres's relational logic implementation makes for a very good queueing system for most cases. It's not a hack that's bolted on top. I know that's how quite a few "DBs" are designed and implemented, and maybe you've been burned by too many of them, but Postgres is solid. I've seen it inside and out.
My point is that postgres is a swiss army knife and you and anyone else would be remiss to not fully understand what it is capable of and what you can do with it. Entire classes of software baggage can be eliminated for "most" use cases. One could even argue that reaching for all these extra fancy specialized tools is a premature optimization. Plus, who could possibly argue against having fewer moving parts?
Sometimes I agree with best tool for the job; if the constraints make something a very clear winner; if the difference is marginal for the particular case at hand, I pick what I/we know (I would actually argue that IS the best tool for the job; but in absolute 'what could happen in the future' terms it probably is not).