Earlier quoted context omitted.
Fair warning, I had serious scaling issues with Timescale. Solutions like Grafana Mimir, Victoria Metrics, Clickhouse, or yes, the new Influx implementation, are much more scalable and will give you much fewer headaches. ClickhouseDB is realy brilliant, btw, it's a powerhouse. Especially with the fairly recent additions that enable hybrid local + S3 option, pushing older metrics to S3 for cheap long-term storage.
The cloud storage option for CH looks like a game changer for time-based data. Any concerns there about accidentally causing "trashing" when cold data is needed? I believe the MergeTree system works by splitting the table into parts during insertion that then later get merged together, so you have to careful that during merging, only the "hot" data is touched, otherwise you'll start pulling in cloud storage data that…
But there are lots of approaches, depending on your needs.
You can (should) define a "cache disk" for S3, which will cache up to X Gb locally to avoid trashing.
Another option is is to move data into separate (purely S3 backed) tables after a certain time to avoid accidentally fetching large amounts of data from S3. You can still easily join the data together if needed.