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Hi Ilya,

Interresting, thanks for sharing.
So the quick conclusion to your numbers seems indicated that mongodb is
more efficient for both reading and writing,
except for 2 cases for retrieving data (meters and resouces listing) ..

However for the reading operations,
it's should be confirmed (or precised) where the time is really spent,
would be interresting to compute the distribution of times spent by each
layer : backend -> api -> cli  .. similarly to what you did for collector
by custom logging (or by instrumentation..)
To add additional use cases (and to be more relevant) it will be good to
use queries executed by billing systems or the alarm evaluator aka
filtering a limited subsets of samples (by resource and/or user and/or
tenant) .. to see the numbers without retrieving ten of thousands of
samples.

btw, others indicators should help to give a good picture, I see for now:
errors rate, queue lenght (rabbit), returned samples|meters|resources by
API calls, missing samples (after the populating)
and some system metrics also.

what was the caracteristics of serveurs used for these load test?

my two cents.
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