Postgres all the way down

The "Postgres for everything" argument is technically seductive but practically brittle. Yes, pgvector and pgmq eliminate network hops and reduce operational surface area. But the real cost isn't CPU cycles or storage-it's contention. A single Postgres instance handling OLTP, search, queues, and analytics inevitably forces tradeoffs in every dimension: you tune for latency on writes and suddenly your vector recall degrades; you scale read replicas and your queue visibility windows drift. I've watched teams burn months on this path. The breaking point is always the same: failure isolation. When a rogue full-text search query spikes IOPS and blocks your critical payment inserts, you don't need a better query planner-you need a separate system. Postgres is a marvel of engineering, but it's a single-process architecture at heart. You cannot partition memory, CPU, or storage per workload without complex extensions that often behave differently under load than advertised. The real question isn't "can Postgres do it?"-it clearly can. It's "at what scale does the operational debt of a monolith outweigh the cognitive debt of multiple systems?" For most teams below 10k requests/second, the answer is never. But if you're building for growth, please measure your blast radius before committing. A queue that crashes your primary database isn't a simplification-it's a single point of failure dressed up as elegance.