Re:Ask HN: How to store billions of rows of time-series data?
by mfreed on Thursday April 09, 2020 @12:45AM
(#22819854)
(Timescale person here.)
Many of our users store many billions of rows + 10s of millions per day. Native compression will give you significant storage savings, and very flexible options for indexing to support various queries. And if you have some things which are commonly queried, easy to build automated continuous rollups (e.g., to continuous rollup to OHLCV candlesticks).
Can deploy either self-managed or Timescale Cloud (timescale.com/cloud), where you can find deployments within $100s per month.
Many of our users store many billions of rows + 10s of millions per day. Native compression will give you significant storage savings, and very flexible options for indexing to support various queries. And if you have some things which are commonly queried, easy to build automated continuous rollups (e.g., to continuous rollup to OHLCV candlesticks).
Can deploy either self-managed or Timescale Cloud (timescale.com/cloud), where you can find deployments within $100s per month.
Cheers!