Just to clarify here, the original post from Aliaksandr was from before Timescale released compression, so that was true at the time, in fact the large amount of storage space used was one of the main reasons we developed compression. With compression it is no longer true. You can take a look at blog posts here: https://blog.timescale.com/blog/building-columnar-compression-in-a-row-oriented-database/ and https://blog.timescale.com/blog/time-series-compression-algorithms-explained/ for some more information on the ways we do that. We also have Promscale now: https://github.com/timescale/promscale which automatically compresses data, uses a specially developed schema for storing Prometheus data and with which you can easily set up and run your own test to see how well it does in terms of space utilization. I'd let it run for a little bit (say a couple days) before comparing as we do maintain a region of uncompressed data in the recent past. Hope that helps clarify.
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