I recently set it up as the ingestion point for an IOT pipeline that currently runs steadily at a high volume, and found that Cosmos would charge me $15k/month

I recently set it up as the ingestion point for an IOT pipeline that currently runs steadily at a high volume, and found that Cosmos would charge me $15k/month in RUs to achieve stable ingestion (i.e., no 429s on intermittent spikes). This was fed by Stream Analytics fed by an eventhub. For comparison, I had the same eventhub feed Kafka Connect to dump it into Mongo 5.0's new timestream collections on a $200/month VM, and after running both outputs at full volume for a couple days, Azure offered me a helpful suggestion to downsize the under-utilized VM and save money. I haven't quite figured out if the RU rate is just too high to be economical, and counts on large orgs with large data to expect a large bill; or if the RU model simple works badly for high velocity data. I've verified that the pricing model now scales down properly for small/medium loads, at which point the various high availability/geographcial distribution features really add value. I'm trying to conceptualize how the RU cost, amortized across longer term storage and less demanding ingress/egress schedules, can work out. For our scenario, Cosmos functionally offers exactly the horizontal scalability we need. As a different sanity check, I set up a SQL Server account as the ingestion database and saw comparable costs, so it wasn't that Cosmos itself has an unworkable pricing model.