Is it really that different from, say, the way Prometheus supports histogram-based quantiles? https://prometheus.io/docs/practices/histograms/

Granted, it looks like Monarch supports a more cleanly-defined schema for distributions, whereas Prometheus just relies on you to define the buckets yourself and follow the convention of using a "le" label to expose them. But the underlying representation (an empirical CDF) seems to be the same, and so the accuracy tradeoffs should also be the same.