I don't know TimescaleDB but PipelineDB is more about real time constant aggregation. You can do like a rolling sum that's has many inserts a second for a very long time, and the speed of retrieving the sum and inserts remain pretty constant.
This approach dramatically limits disk IO and long-term storage requirements, and enables super high performance in most cases on modest hardware.
PipelineDB has been used in production for nearly four years now and is used by Fortune 100 companies.
My hunch says that it's possible as far as there is some additional computation done with the future aggregate query on the coordinator in Citus.
PPDB looks interesting, but we also need to keep the underlying raw data and multiple clusters require more complex pipeline.
One thing I will mention here is that we do have plans to add support for persistent streams [0] after version 1.0.0 is released. We've learned a lot over the years about how our users/customers interact with streams in production and persistent streams will be built atop that foundation of understanding.
Please feel free to comment on that issue with your use case, requirements, etc. and we'll see what we can do!
A pair of both would only be missing an in-memory and on disk column-oriented 'analytics' tier (perhaps as separate instance that's being continuously fed from the first two?).
I think I had seen that PostgreSQL also has columnar store extension, wondering if that would work close the remaining gap for the analytics instance.