Hi,
TimescaleDB as a Postgresql extension has been used in my firm for two years now, I've recently managed to upgrade it from pg10 to pg12 and from discrete VM's to Kubernetes as well.
Frankly speaking, being new to TimescaleDB at that time, I've found it easy to manage, easy to scale (it's 100% compatible with pg replication, unfortunately not the logical one, yet...), easy to install, easy to upgrade... what else?
From a developer's perspective, it just adds "superpowers" to ordinary PG tables, all under the hood. On disk, it features a "chunked" layout, where each chunk belongs to a definite "time" range; and of course the "time" column on which to index time data is just passed as a parameter to the call to TimescaleDB, for each table on which you need such power.
At the moment, we're also using it for time aggregate calculations, but only for the coarse ones (30m --> 1h and 1h --> 1 day), while we're still handling the finer ones (1s --> 1m and so on) in Kafka+Flink, which is a common scenario for a streaming data platform, anyway.
Regards,
Adalberto
Dear All,
I'm Jayaram S, oracle DBA. Currently we are planning to develop a stock market based application which deals 80% of data with time data. We are in the process of choosing the right database for the requirement especially for time series data. After all multiple investigations, I found PostgreSQL with timescaleDB works better than other DBs.
But still I'm new to PGSQL and we wanted only open source technology to handle our requirements. It will be helpful to me if anyone can suggest implementing the time series concepts in PostgreSQL database.
It's better if I can get proper docs or links with explanation.
Thanks in advance.,
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Thanks & Regards,
Jayaram S,
Banglore.
India.
