Earlier quoted context omitted.
Not really true. I point whatever thing that talks something like influx to it with the right credentials and it outputs whatever metrics it wants to it. No need to manage/pre-create all your tables for every single possible metric out-there. I seriously dislike nosql databases for most purposes, and am absolutely a Postgres fan - but timeseries is the only thing I've encountered that benefits from a dedicated schema…
How's that any different than something that talks SQL? It's the most universal data language there is. Why do you have to make new tables? It's 1 table with timestamp , name , value to store all your metrics and you can use an array or json column if you have extra non-structured data. Add in the SQL joins and analysis and you get a much better tool for timeseries.
To use SQL you need to know the schema you're working against. Every single tool has to agree on a specific schema - and there are tons of existing tools that push infrastructure/system metrics into timeseries databases. For them it's simple, Influx uses some API, OpenTSDB uses another, Prometheus uses yet another - but they're all pretty simple to use. If you would point them to a Postgres database on the other hand, they wouldn't have a clue what fields to insert.