PipelineDB was useful primarily if you primarily wanted to maintain a _continuous_ materialization of some aggregate (e.g., an approximation of the distinct ite

PipelineDB was useful primarily if you primarily wanted to maintain a _continuous_ materialization of some aggregate (e.g., an approximation of the distinct items in the database), not necessarily an aggregate per time period. If you are interested in primarily showing the recent data -- which you see in many monitoring examples in IT/devops or IoT -- you often want the raw data or an aggregate per time period. As an aside, TimescaleDB introduced continuous aggregations in v1.3. Here's a nice example of using it with Grafana for dashboarding: https://blog.timescale.com/blog/how-to-quickly-build-dashboards-with-time-series-data/ https://blog.timescale.com/blog/how-to-quickly-build-dashboa...