PostgreSQL for Everything

	PostgreSQL for Everything(raphaelbauer.com)
	428 points by karlmush 2 days ago \| 257 comments
	tl;dr: PostgreSQL can replace many specialized systems in your stack: full-text search (Solr/Elastic), document storage (MongoDB), message queues (Kafka/RabbitMQ via SELECT FOR UPDATE SKIP LOCKED), time-series data (Clickhouse via TimescaleDB), vector DB for AI (pgvector), caching (Redis via UNLOGGED tables), graph data (LTREE), and even microservices (JSON query results). The argument: it's rock-solid, easy to run everywhere, and consolidating on Postgres dramatically simplifies your infrastructure—start there and only adopt specialized tools when you actually outgrow it.
	HN Discussion: ↑Real-world examples like Revolut prove Postgres can handle these varied workloads at scale ↑Start with Postgres by default and only adopt specialized tools when you hit actual limits ↓Postgres is not a real replacement for specialized tools like Elastic or Kafka beyond basic use cases ↓The 'one tool for everything' framing is a hammer-nail fallacy; best-of-breed tools exist for good reasons ~Agrees in principle but flags caveats around message queues, time-series, vectors, and ecosystem tooling support