From: | Erik Serrano <eserranos(at)gmail(dot)com> |
---|---|
To: | Rui DeSousa <rui(at)crazybean(dot)net> |
Cc: | Keith Fiske <keith(dot)fiske(at)crunchydata(dot)com>, Samed YILDIRIM <samed(at)reddoc(dot)net>, Pgsql-admin <pgsql-admin(at)lists(dot)postgresql(dot)org>, pgsql-admin <pgsql-admin(at)postgresql(dot)org> |
Subject: | Re: PostgreSQL historical database |
Date: | 2024-11-16 13:41:29 |
Message-ID: | CA+dvXXugr9a5xCi95hsi5_FKTpYvM3WDg6EdgAGacwOp-5YkqA@mail.gmail.com |
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Thread: | |
Lists: | pgsql-admin |
Muchas gracias, Michel . Saludos
El vie, 15 nov 2024, 19:52, Rui DeSousa <rui(at)crazybean(dot)net> escribió:
>
>
> On Nov 5, 2024, at 1:15 PM, Keith Fiske <keith(dot)fiske(at)crunchydata(dot)com>
> wrote:
>
> I would first recommend looking into partitioning for managing data
> retention like this.
>
>
> I don’t think you need partitioning. The is so many ways to slice this
> problem.
>
> You need some form of logical replication. I’ve used both of these
> methods in the past to do exactly the issue at hand. These are not the
> only solutions.
>
> 1, Queue tables via triggers and then asynchronous replicate those
> transaction to the archive database in real time.
> 2. Messages queues; Modern application make use of massage queues; Just
> attach the archive database to the same message queue.
>
> I don’t see a need for partitioning. I managed a Muti-terabyte content
> delivery platform where the data was only licensed between 30 to 90 days.
> Records where being purged more or less just as fast as new records were
> being created. In essence the database was completely reloaded with new
> data every 30-90 days depending on the data stream. We did no use any form
> of partitioned tables and had no performance issues.
>
>
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