It depends on your use case. For example, Postgres will hit limitations for large streams of time series data on the ingestion side, and the standard SQL language of Postgres may make it challenging to navigate a dataset by time: sampling the data, time intervals, time-series joins (ASOF join), and these kinds of things are not easy or possible to do on Postgres.

Why not combine Postgres for OLTP workloads alongside another database for fast analytics/time series, optimised to deal with high throughput ingestion and low latency queries?

NB: I am one of the co-founder of an open-source time series database (questdb)