This is the blog post that Rakesh referenced: https://blog.timescale.com/time-series-data-postgresql-10-vs-timescaledb-816ee808bac5
Please note, this analysis is done in the context of working with time-series data, where 1000s of chunks is not uncommon because of the append-mostly nature of the workload. On Mon, Jan 8, 2018 at 6:54 PM, Rakesh Kumar <rakeshkumar...@mail.com> wrote: > > You should have read carefully what I wrote. 1000 is not an upper > limit. 1000 partition is the number after which performance starts > dropping . > > There is a blog in www.timescale.com which also highlights the same. > > Sent: Monday, January 08, 2018 at 6:20 PM > From: "Kumar, Virendra" <virendra.ku...@guycarp.com> > To: "pgsql-gene...@postgresql.org" <pgsql-gene...@postgresql.org> > Subject: How Many Partitions are Good Performing > > Can somebody tell us how many partitions are good number without impacting > the performance. We are hearing around a thousand, is that a limit. Do we > have plan to increase the number of partitions for a table. We would > appreciate if somebody can help us with this? > > Regards, > Virendra > > > ------------------------------------------------------------ > This message is intended only for the use of the addressee and may contain > information that is PRIVILEGED AND CONFIDENTIAL. > > If you are not the intended recipient, you are hereby notified that any > dissemination of this communication is strictly prohibited. If you have > received this communication in error, please erase all copies of the > message > and its attachments and notify the sender immediately. Thank you. > > -- TimescaleDB* | *Growth & Developer Evangelism c: 908.581.9509 335 Madison Ave. New York, NY 10017 http://www.timescale.com/ https://github.com/timescale/timescaledb
