Timescale way to explore https:https://cdn.v2ex.com/navatar/766d/856e/1014_normal.png?m=1584593899 https:https://cdn.v2ex.com/navatar/766d/856e/1014_large.png?m=1584593899 2020-03-19T06:27:19Z Copyright © 2010-2018, V2EX TimescaleDB 1.5 里新增了压缩功能 tag:www.v2ex.com,2020-03-19:/t/654205 2020-03-19T05:01:45Z 2020-03-19T06:27:19Z Livid member/Livid
时序类型的数据,本来就会越用量越多,这个压缩功能看起来效果不错:

https://docs.timescale.com/latest/using-timescaledb/compression

实际压缩效果:

https://twitter.com/thursdayschild/status/1239918746598334465 ]]> timescale scale out tag:www.v2ex.com,2018-12-22:/t/520031 2018-12-22T09:20:43Z 2018-12-22T09:17:43Z funky member/funky Timescale tag:www.v2ex.com,2018-03-08:/t/436365 2018-03-08T22:36:59Z 2018-03-09T02:16:03Z Livid member/Livid
https://www.timescale.com/

这是一个用各种时间维度查询纽约市出租车出行数据的例子:

https://docs.timescale.com/v0.9/tutorials/tutorial-hello-nyc

如果你的数据类型就是各种数值 + 时间(比如各种计费数据或是来自传感器的数据),那么 Timescale 会是一个很值得尝试的方案。 ]]>
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