Yeah, I would be really interested in hearing any arguments that would invalidate my research (because hey, if InfluxDB would actually be a good fit for long-te

Yeah, I would be really interested in hearing any arguments that would invalidate my research (because hey, if InfluxDB would actually be a good fit for long-term storage of Prometheus metrics, that'd be awesome, because it's Go and easy to operate). However, if the data model didn't change fundamentally (the fundamental InfluxDB record being a row containing full key/value metadata vs. Prometheus only appending a single timestamp/value sample pair for an existing time series whose metadata is only stored and indexed once), I wouldn't expect the outcome to be qualitatively different except that the exact storage blowup factor will vary. Interesting to hear that InfluxDB is using BoltDB now. I benchmarked BoltDB against LevelDB and other local key-value stores around a year ago, and for a use case of inserting millions of small keys, it took 10 minutes as opposed to LevelDB taking a couple of seconds (probably due to write-ahead-log etc.). So BoltDB was a definite "no" for storing the Prometheus indexes. Also it seems that the single file in which BoltDB stores its database never shrinks again when removing data from it (even if you delete all the keys). That would also be bad for the Prometheus time series indexing case.