pg_partman VS TimescaleDB

Assuming these are the types of insights you're looking for, you'll probably look for a way to aggregate data points across/within geographies. postgis is an open source extension for postgres that can help you with this, but there's also quite a few python tools that can help you explore the data, such as geopandas, folium, geoplot. Depending on volume, you might want to partition the data for query performance, and there's another extension pg_partman that can help with that. Just noticed some other posts have recommended something similar.

pg_partman is in RDS >12.5 (here). Pg_partman makes managing data retention relatively easy.

Whenever I see these posts from TimescaleDB, I always want to ask them how it compares in performance to alternative extensions that implement the same features, rather than just comparing TimescaleDB to vanilla PostgreSQL.

For example, they mention their automated data retention and how it's achieved with one SQL command, and how DELETEing records is a very costly operation, and how "even if you were using Postgres declarative partitioning you’d still need to automate the process yourself, wasting precious developer time, adding additional requirements, and implementing bespoke code that needs to be supported moving forward".

There's zero mention anywhere of pg_partman, which does all of these things for you equally as simply, and is a fully OSS free alternative [0].

I get that it's a PG extension that competes with their product. I know that TimescaleDB does a few other things that pg_partman does not. But I can't help but find its (seemingly) purposeful omission in these, otherwise very thorough blog posts, misleading.

[0] https://github.com/pgpartman/pg_partman/blob/master/doc/pg_p...

Take a look into this extension which would take care of a good amount of automation for you.

You might want to look into pg_partman which has many useful tools around semi-automatic partitioning. According to their documentation they already have a procedure that will do exactly that: create new partitions based on the rows in the default partition.

Don't forget PostgreSQL extensions. For something like a chat log, TimescaleDB (https://www.timescale.com/) can be surprisingly efficient. It will handle partitioning for you, with additional features like data reordering, compression, and retention policies.

Offboard it to Postgres specialists like https://www.timescale.com/

TimescaleDB{:target="_blank"}: an extension of PostgreSQL that adds time-series capabilities to the relational database model. It provides scalability and performance optimizations for handling large volumes of time-stamped data while maintaining the flexibility of a relational database.

Have some experience with https://www.timescale.com in this context

What about getting in touch with commercial organisations that have products/services based on PostgreSQL? For example Timescale, EDB, and Citus Data, or really any hosting provider that offers a managed PostgreSQL service.

There is Timescale.

Friends don't let their friends choose Mysql :)

A super long time ago (decades) when I was using Oracle regularly I had to make a decision on which way to go. Although Mysql then had the mindshare I thought that Postgres was more similar to Oracle, more standards compliant, and more of a real enterprise type of DB. The rumor was also that Postgres was heavier than MySQL. Too many horror stories of lost data (MyIsam), bad transactions (MyIsam lacks transaction integrity), and the number of Mysql gotchas being a really long list influenced me.

In time I actually found out that I had underestimated one of the most important attributes of Postgres that was a huge strength over Mysql: the power of community. Because Postgres has a really superb community that can be found on Libera Chat and elsewhere, and they are very willing to help out, I think Postgres has a huge advantage over Mysql. RhodiumToad [Andrew Gierth] https://github.com/RhodiumToad & davidfetter [David Fetter] https://www.linkedin.com/in/davidfetter are incredibly helpful folks.

I don't know that Postgres' licensing made a huge difference or not but my perception is that there are a ton of 3rd party products based on Postgres but customized to specific DB needs because of the more liberalness of the PG license which is MIT/BSD derived https://www.postgresql.org/about/licence/

Some of the PG based 3rd party DBs:

Enterprise DB https://www.enterprisedb.com/ - general purpose PG with some variants

Greenplum https://greenplum.org/ - Data warehousing

Crunchydata https://www.crunchydata.com/products/hardened-postgres - high security Postgres for regulated environments

Citus https://www.citusdata.com - Distributed DB & Columnar

Timescale https://www.timescale.com/

Why Choose PG today?

If you want better ACID: Postgres

If you want more compliant SQL: Postgres

If you want more customizability to a variety of use-cases: Postgres using a variant

If you want the flexibility of using NOSQL at times: Postgres

If you want more product knowledge reusability for other backend products: Postgres

TimescaleDB is Postgres with extensions to automatically partition tables for fast processing of time series data.