pg_auto_failover VS amazon-redshift-utils

pg_auto_failover makes it an absolute breeze. I cannot understand how it's not mentioned in the article.

I've been runnning it for 3 years with great success - https://github.com/hapostgres/pg_auto_failover/discussions/6...

Simplified and probably OK: pg_auto_failover - One Monitor/Witness node and minimum services otherwise. Good documentation to get started and not nearly as complex as Patroni.

There are tools that make managing such a system easier. Check out patroni, pg_auto_failover or PAF

This is /extremely/ uncharitable. It depends more on the project.

For example, both Go and .NET are very well written with comprehensible documentation. Many projects have also been absorbed by the Apache Foundation or other FOSS initiatives.

Every FANG has boat loads of teams working on umpteen different open source packages. The quality naturally varies.

Let me pick two more esoteric projects as a point of comparison.

Yandex Odyssey (https://github.com/yandex/odyssey) an advanced multi-threaded PostgreSQL connection pooler and request router. Figuring out how exactly and when to use this is not quite clear. There is no "getting started" guide for this package. There is barely any explanation for how it works or what it does.

pg_auto_failover (https://github.com/citusdata/pg_auto_failover) run by Citus (owned by Microsoft) monitors and manages automated failover for a Postgres cluster. This repo even has diagrams explaining the workflow and complete instructions.

Right, https://github.com/citusdata/pg_auto_failover has been on my reading list

My go to for this is https://github.com/citusdata/pg_auto_failover set up with ansible https://github.com/neuroforgede/pg\_auto\_failover\_ansible

pg_auto_failover github | readthedocs | ytube

AWS has a Redshift utility script to run checks on what tables can be regularly analyzed and / or vacuumed based on certain set of thresholds. This can be run as a part of a monthly / periodical cluster maintenance.

I always install https://github.com/awslabs/amazon-redshift-utils/tree/master... on my Redshift clusters.

What you are describing as code reuse exists for databases, but they are called applications and generally utilize a general purpose programming language. It doesn’t make sense to have a SLA data model library because every use case is different. It’s a database, not procedural code.

https://github.com/awslabs/amazon-redshift-utils/blob/master...

The compression actually works as advertised, but you can compress so well that the database ends up retrieving too many blocks from the other columns in your query.