Ask HN: What is the best DB for versioned time series?
Dear all,
time series DBs are a hot topic these days but given the focus on IoT -- or more generally measurement data -- the underlying data model typically assumes that for one time series there is only one data point per period of time, so it's really just one dimensional. However, if you work for example with forecast data (say for a stock price) you might wanna store every version of a forecast and not overwrite the previous forecast. What are in your experience the best time series databases that (natively) support two or more dimensions and also allowing queries on these other dimensions like "get forecast for delivery-time from x to y where forecast_time = z"?
Thanks! sambucini
https://spotify.github.io/heroic/ is a multi dimensional timeseries database with a rich query language.
I have been using the ELK stack as a time series database for a long time, I know it isn't built for it but there's so much documentation and resources online that makes it a very "easy" choice, it's very easy to scale any part of it, use the elastic as a nosql database, have kibana to visualize and easily query. Curator to move old data to cold storage / shrink. It's been a no brainer.
Have a look a TimescaleDB.
I've used this with decent success. Their support slack channel is great as well, and there is a lot of active development on the project.
Postgres's built in partitioning is also being actively developed. If it gets good enough, I wonder what will happen to timescaleDB as a company...
Wouldn't that be solved with tags? Most time series databases support tagging values.
Yeah. You can treat the version as just another attribute to identify the series.
Amazon just launched their Time Series DB. It is probably worth a look.
Clickhouse - https://clickhouse.yandex
Great, thanks all!