You know that sinking feeling when you’re halfway through a Node.js project and someone says, ‘We need a job queue.’ Your brain immediately goes to Redis—because that’s what everyone does. But then you remember: another service to configure, another memory-hungry daemon to babysit, another point of failure at 3 AM.
There’s a better way. And it’s been sitting in your stack all along.
Most teams adopt Redis for job queues not because their scale demands it, but because it’s the path of least resistance. CatQueue is a PostgreSQL-based job queue for Node and TypeScript that removes Redis entirely. It bets that for a huge class of real-world workloads, PostgreSQL’s reliability and developer familiarity are enough. And it’s winning that bet.
I’ve been there. You’ve probably spent hours debugging a Redis connection pool, or watching your memory usage spike because of a misconfigured TTL. The relief of simplifying your stack—removing a flaky, memory-hungry dependency—is real. CatQueue gives you that relief without sacrificing the core functionality you actually need: reliable job processing, retries, concurrency control.
The real complexity in most systems is self-imposed infrastructure overhead, not throughput. CatQueue exposes that. If your application processes thousands—not millions—of jobs per day, Postgres handles it gracefully. You already have Postgres running. You already know how to query it. So why add another moving part?
Sure, there’s a twist. The very scalability limits that pushed teams toward Redis may reappear as Postgres becomes the bottleneck under load. When you’re handling a million jobs an hour, Postgres will sweat. But here’s the honest question: are you actually there? Or are you optimizing for a future that may never arrive?
Be honest about when Postgres stops being enough—but don’t assume it’s inadequate until you’ve measured. CatQueue isn’t for everyone. It’s for the developer who wants to ship a job queue today without provisioning a new database, without learning a new API, without adding operational debt. It’s for the team that values simplicity over premature optimization.
One developer who tried it said: ‘I personally like simple database queues when there are not a lot of jobs. Will check this one out.’ That’s the right mindset. Start simple. Add complexity only when you need it.
So next time you reach for Redis, pause. Ask yourself: do I need the overhead, or do I just need a queue? CatQueue is a reminder that the best tool is often the one you already have.
FAQ
Q: What happens when my Postgres database becomes the bottleneck under high load?
A: Then you scale. CatQueue is designed for workloads where Redis is overkill—not for millions of jobs per hour. When you hit that limit, you can migrate to a more specialized queue. But don't optimize for a load you don't have yet.
Q: Is CatQueue production-ready?
A: The GitHub repo shows it's actively maintained and used by the author. As with any open-source tool, evaluate it against your specific requirements. It's a solid choice for small-to-medium scale systems where operational simplicity is a priority.
Q: Why not just use Redis? Isn't it faster?
A: Redis is faster at raw throughput, but speed isn't everything. The operational cost of running Redis—memory limits, persistence quirks, connection management—often outweighs the performance gain for typical job queues. CatQueue trades some peak throughput for a much simpler stack.