View the Call for Papers page .
Time: 15:35 - 16:25
One of the limiting factors of most timeseries databases is that, in order to get good read performance, they limit your ability to update data. That's fine if your data is an event stream, but if its coming from a pre-aggregated sources it might update past data, for example data about online ad performance updated after click fraud is discovered. In this talk I'll show you how AdStage stores timeseries data in Postgres to allow fast reads and updates using clever scheme design and functions for speed.
The following slides have been made available for this session:
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