[mfreed]

@ekzhu At this point, this is mostly about the "developer experience" for doing time-series analytics within SQL - as you point out - ability to "short-cut" complicated SQL queries.

We actually heard something similar about SQL vs. PromQL - for the more limited domain that PromQL operated in, people really like how simplified it was. (We've also built an observability platform Promscale on top of TimescaleDB [0].) This is one take on bringing this type of simplicity & pipelined analytics to SQL, while remaining fully SQL compliant.

I also hope this isn't out of place, but if these types of problems interest you, we're always looking for great people (and lots of folks here have a research background). Shoot me a note:

mike (at) timescale (cofounder/CTO)

[0] https://www.timescale.com/promscale

[ekzhu]

Thanks for the response. I enjoy reading your blog. What you said reminds me of the post [0] in which you compared Timescale with InfluxDB and argued that SQL is better. Has your position changed due to new observation regarding usability?

[0] https://blog.timescale.com/blog/sql-vs-flux-influxdb-query-l...