Neues vom PostgreSQL Planet

In the previous post, I explored some nuances of Postgres related to indexes and parallel workers. This text sparked a lively discussion on LinkedIn, during which one commentator (thanks to Ants Aasma) proposed an index that was significantly more efficient than those discussed in the article.

PostgreSQL is built to perform. However, as workloads increase and systems evolve, even the most robust setups can begin to show signs of strain. Whether you are scaling a product or supporting enterprise SLAs, performance slowdowns tend to surface when you least want them to.

If you are a technology leader overseeing a team of developers who manage PostgreSQL as part of a broader application stack, or you are responsible for uptime and customer satisfaction at scale, knowing where to look first can make all the difference.

Introduction

The importance of backups is universally acknowledged in our digital world. One of my former esteemed colleagues told me that he can't think of a database system without backups. This perspective has resonated with me over the years. Today, in our CNPG series, we will be taking a look at the backup solution and how we restore a database from the backup.

     Authors find it challenging to write a comprehensive book about PostgreSQL for several reasons. The first is that a new version of PostgreSQL is released every year with changes, new features, and tweaks.  I am lucky to have been able to review several new database titles each year, and I would like to let you know that Hans-Jurgen Schonig's Mastering PostgreSQL is a well-written reference. 

PostgreSQL has a fairly efficient buffer manager that handles data movement between shared memory and disk storage. Among other things, its primary purpose is to serve as a disk cache for the client backend processes for quick access to data. The size of this buffer is dictated by the setting shared_buffers in postgresql.conf, and its default value is 128 MB.

Broadcasting a quick tip from a real-life “tasklet” where a customer was genuinely surprised why a seemingly logical fix didn’t show up on Google / LLM-s. So let’s see if we can improve on that situation. So in short a large central table was getting too bloated (fragmented) and query...