4 ms·
In my opinion you're correct, it doesn't solve the problem of querying large sets of timeseries data over a long time span. It doesn't pre-aggregate your data
by thisone 7y ago
In my opinion you're correct, it doesn't solve the problem of querying large sets of timeseries data over a long time span.
It doesn't pre-aggregate your data so if you're trying to get aggregates for a large data set, it's not fast.
- akulkarni 7y ago(Co-founder TimescaleDB) Pre-aggregation via continuous aggregations is in our next release, which I believe is slated for Monday. We also have more in the works for large datasets: eg scaling out storage across multiple machines as well as data tiering for lower storage costs. Feel free to email me if you'd like more info on either: ajay (at) timescale (dot com)
- djk447 7y agoHi! Engineer at Timescale who’s just been working on this feature, it’s coming in our next release and going to continue to be developed over the next few releases! Would love to have you try it out and get your feedback :)
- scrollaway 7y agoGod I love you folks. I can't wait for timescale to be available on rds, the more I read about it the more I love it and its authors.
- shin_lao 7y agoThanks for the feedback. How is TimescaleDB doing with compression by the way? Meaning if you compare your raw data and the disk usage, what's the ratio?
- akulkarni 7y agoYou can get 6-8x compression by running on TimescaleDB on ZFS, but compression in general is also an area where we are investing a fair amount of R&D. Also worth noting that TimescaleDB is far more memory-efficient than other time-series databases (eg InfluxDB [1]), and for some folks the memory cost savings is significant (b/c memory cost $$$ >> disk cost $). [1] https://blog.timescale.com/timescaledb-vs-influxdb-for-time-series-data-timescale-influx-sql-nosql-36489299877/ https://blog.timescale.com/timescaledb-vs-influxdb-for-time-...