pg_bitemporal VS temporal_tables

I feel like i keep yelling the following, but bitemporal tables.

- https://aiven.io/blog/two-dimensional-time-with-bitemporal-d...

- https://github.com/scalegenius/pg_bitemporal

4 timestamps and some ugly queries.

People here may also be interested to see this analysis of the state of SQL:2011 "temporal table" feature adoption: https://illuminatedcomputing.com/posts/2019/08/sql2011-surve...

I don't think much has really changed since, and I'm not sure Postgres is any closer to addressing this natively (although there have been extensions, e.g. https://github.com/scalegenius/pg_bitemporal).

Something more sophisticated would be https://github.com/scalegenius/pg_bitemporal

Sure, I can appreciate that native support for a feature like this is nice.

As I understand it, most implementations (including another one for bitemporality[1]) involve either audit tables, as you mention, and/or additional support columns. It's as if the "now" representation is simply a narrow lens onto the underlying data.

That said, PostgreSQL encodes and has battle-tested decades of database functionality including an ecosystem around those, so I'd be a little wary of switching technology even if it does solve one individual problem thoroughly. Everything has to start somewhere, though.

[1] - https://github.com/scalegenius/pg_bitemporal

There is also the temporal_tables extension.

[0] https://github.com/arkhipov/temporal_tables

- https://github.com/arkhipov/temporal_tables

I haven't used any of these but I work on https://xtdb.com which is also implementing SQL:2011's temporal features :)

It seems like PG has this extension here anyone ever use it?

You could look at that or ask me questions about it (disclaimer, I am the author). Also there is https://github.com/arkhipov/temporal_tables/

All good. Note there is also https://github.com/arkhipov/temporal_tables/ (which is also type 4 as a postgres extension - pretty similar to what ebean orm is doing)

The Temporal Tables Postgres extension works well. https://github.com/arkhipov/temporal_tables

If you're doing this across regions, you really really should reconsider. If you're doing it in the same data center you might be able to get away with it (but then I'm not sure why you're doing it in the first place, if the system fits in one DC then you probably can just scale up). It might be worth considering a sharded & passively combined approach -- i.e. every country has it's own data, and there's some huge public schema which consists of all the data that is drip fed in to materialized views or tables at regular intervals. You could also combine this with temporal_tables to get a very delayed but theoretically time-consistent (well, aside from clock skew across regions of course...) view of your DB to query... Really depends on the use case.

One of postgres's most underrated features. RLS is amazing, can be unseen/basically work silently if your programming language-side tools are good enough, and is documented well (like everything else):

https://www.postgresql.org/docs/current/ddl-rowsecurity.html

But the power of PG is that it doesn't stop there, if you combine this with a plugin like temporal_tables and you can segment by user and time:

https://github.com/arkhipov/temporal_tables

All of this mostly unknown to the thing that's accessing the DB. If that's not enough for you, why not add some auditing with pgaudit:

https://www.pgaudit.org/#section_three

I think it might not actually be hyperbole to say that Postgres is the greatest RDBMS database that has ever existed.