[grammr]

PipelineDB co-founder here--I think this is a pretty fair take! I would also like to point out that the aggregate data stored in PipelineDB can still be further aggregated, processed, JOINed on etc. on demand as well.

Since a continuous view's output is simply stored as a regular table, you are free to run arbitrary SELECT queries on it to further distill and filter your results. PipelineDB's special combine [0] aggregate allows you to combine aggregate values with no loss of information for this very purpose.

The most common pattern among our user base is to aggregate time-series data into continuous views at some base level of granularity (e.g. by minute) and then aggregate over that for final results (e.g. aggregate down to hour-level rows for the date range my frontend has selected).

[0] http://docs.pipelinedb.com/aggregates.html#combine