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This is something i've been meaning to look into for a personal project that has a lot of time series data. It'll be interesting to see what they eventually co
by Tostino 9y ago
This is something i've been meaning to look into for a personal project that has a lot of time series data. It'll be interesting to see what they eventually come up with to make time series data not take quite as much space.
- mfreed 9y agoHi Tostino, please let us know how things work. Regarding compression: While we haven't yet built in any native compression, we regularly run on ZFS and typically get 3-4x compression using that. (Plus with ZFS, insert rates are actually a bit faster, at least when using a single disk (often 25%). It's definitely something to consider.) Another thing to consider is that Timescale supports easy data retention policies, which can also vary by hypertable (i.e., keep raw data for 1 month, aggregated data for 1 year). It also supports many disks per server, either via RAID or through Postgres' tablespace. But now you can have multiple tablespaces in a single "hypertable", rather than just one like normal. So especially in cloud settings, it's pretty easy to just add more and more disks to even a single machine.
- doublerebel 9y agoReally interesting to hear you use ZFS for those benefits. Are you using ZFS on Linux or a Solaris variant?
- RobAtticus 9y agoWe used it on an Ubuntu machine on Azure. We didn't do any real tuning yet, it was just an initial test to ballpark the benefit.