PipelineDB is pretty interesting for time-series data. It takes an approach to processing the data as it comes in, and storing aggregates or pre-aggregates over time series. I haven't followed the latest, but as of a few years ago much of the approach was similar to some research out of UC Berkeley from about 10 years ago. You can find the paper that talks about that work (TelegraphCQ CQ for continuous query) at <a href="http://db.csail.mit.edu/madden/html/TCQcidr03.pdf" rel="nofollow">http://db.csail.mit.edu/madden/html/TCQcidr03.pdf</a>. Definitely an interesting read if you're into technical papers and databases.
I didn't know the product at all, at a glance this looks amazing to be for BI/alerting on streaming time series data.<p>Anyone who wants to chime in on whether this has fit your requirements for time series data processing? Thanks!
This would be absolutely perfect for the job I had in Sales Intelligence a few years ago... except we were locked into SQL Server and there was no way the powers that be would ever let us switch over to PostgreSQL.
What is storage model compared to timescaledb [0]<p>[0] <a href="https://github.com/timescale/timescaledb" rel="nofollow">https://github.com/timescale/timescaledb</a>