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A time series database is specialized for use cases where the data and query patterns are solely temporal in nature and must show the latest data in real-time (
by abvdasker 7y ago
A time series database is specialized for use cases where the data and query patterns are solely temporal in nature and must show the latest data in real-time (performance metrics/monitoring and stock prices come to mind). Relational and NoSQL databases tend to degrade rapidly with these query patterns at scale (think of the complexity of SQL queries to bucket rows by timestamp).
https://en.m.wikipedia.org/wiki/Time_series_database https://en.m.wikipedia.org/wiki/Time_series_database
- roskilli 7y agoI touch on this a little in the podcast I did with Jeff[0], but it boils down to OpenTSDSB for us when we benchmarked could only do low tens of thousands of writes per second per node, whereas M3DB is hyper optimized and can do hundreds of thousands to millions of writes per second per node depending on compute/disk. Also with a fast inverted index we were able to achieve much faster query times than OpenTSDB at scale. [0]: https://softwareengineeringdaily.com/2019/08/21/time-series-databases-with-rob-skillington/ https://softwareengineeringdaily.com/2019/08/21/time-series-...
- refset 7y agoNote that temporal databases are also a thing, so it's probably wise to avoid using the word "temporal" when discussing time series databases. As far as I know kdb+ is the only technology that has a foot in both camps. https://en.m.wikipedia.org/wiki/Temporal_database https://en.m.wikipedia.org/wiki/Temporal_database
- CharlesW 7y ago> As far as I know kdb+ is the only technology that has a foot in both camps. Teradata Vantage also supports both. And you're absolutely right, it's important not to conflate "temporal" and "time series" support.