I've done small scale experiments with up to 100-500k rows, and did not notice any significant degradation in search query latency - p95 still well under 1s.

I haven't directly compared against Elasticsearch yet, but I plan to do that next and publish some numbers. There's a benchmark harness setup already: https://github.com/getomnico/omni/tree/master/benchmarks, but there's a couple issues with it right now that I need to address first before I do a large scale run (the ParadeDB index settings need some tuning).

we have a pretty intensively used postgres backed app handling thousands of users concurrently. After 6 years and thousands of paying custoners, we are only now approaching to the limits of what it can support on the horizon. TLDR: when you get there, you can hire some people to help you break things off as needed. if you're still trying to prove your business model and carve yoruself a segment of the market, just use postgres

LLM bot.

another AI post...