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Last week I posted about how we often don’t pick the optimal plan. I got asked about difficulties when trying to reproduce my results, so I’ll address that first (I forgot to mention a couple details). I also got questions about how to best spot this issue, and ways to mitigate this. I’ll discuss that too, although I don’t have any great solutions, but I’ll briefly discuss a couple possible planner/executor improvements that might allow handling this better.

PostgreSQL Person of the Week Interview with Josef Machytka: I was born in Czechia and lived most of my life there. However, for the last 12 years, my family and I have been calling Berlin, Germany, our home. It is an open-minded place that gives people a lot of freedom, we like it here very much.

PostgreSQL 19 development is now officially under way, so from now on any new features will be committed to that version. Any significant PostgreSQL 18 changes (e.g. reversions or substantial changes to already committed features) will be noted here separately (there were none this week).

PostgreSQL 19 changes this week

The first round of new PostgreSQL 19 features is here:

A flame graph is a graphical representation that helps to quickly understand where a program spends most of its processing time. These graphs are based on sampled information collected by a profiler while the observed software is running. At regular intervals, the profiler captures and stores the current call stack. A flame graph is then generated from this data to provide a visual representation of the functions in which the software spends most of its processing time. This is useful for understanding the characteristics of a program and for improving its performance.

We are excited to announce the schedule for PGDay UK 2025 has been published. We've got an exciting line up for talks over a range of topics. There will be something for everyone attending.

Take a look at what we have going on: https://pgday.uk/events/pgdayuk2025/schedule/

We'd like to extend our gratitude to the whole CFP team, who did an amazing job selecting the talks to make up the schedule.

A round up of the fifth PGConf.be

The shared presentations are online, as are a couple of recordings and turtle-loading have-a-cup-of-tea locally stored photos.

pgroll 0.14 is released with several new subcommands and better control over how version schema are created.

Recently, we worked with a client who was manually backing up their 800GB PostgreSQL database using pg_dump, which was growing rapidly and had backups stored on the same server as the database itself. This setup had several critical issues:

Having attended PGConf.DE'2025 and discussed the practice of using Postgres on large databases there, I was surprised to regularly hear the opinion that query planning time is a significant issue. As a developer, it was surprising to learn that this factor can, for example, slow down the decision to move to a partitioned schema, which seems like a logical step once the number of records in a table exceeds 100 million. Well, let's figure it out.

Introduction

Over the last decade, when working on databases where UUID Version 41 was picked as the primary key data type, these databases usually have bad performance and excessive IO.

UUID is a native data type that can be stored as binary data, with various versions outlined in the RFC. Version 4 is mostly random bits, obfuscating information like when the value was created, or where it was generated.

PostgreSQL user groups are a fantastic way to build new connections and engage with the local community. Last week, I had the pleasure of speaking at the Stuttgart meetup, where I gave a talk on “Operating PostgreSQL as a Data Source for Analytics Pipelines.”

Below are my slides and a brief overview of the talk. If you missed the meetup but would be interested in an online repeat, let me know in the comments below!

How targeted improvements helped us speed up bulk data loads and complex schemas.

Most teams building production applications understand that “uptime” matters. I am writing this blog to demonstrate how much difference an extra 0.09% makes.

At 99.9% availability, your system can be down for over 43 minutes every month. At 99.99%, that window drops to just over 4 minutes. If your product is critical to business operations, customer workflows, or revenue generation, those 39 extra minutes of downtime each month can be the difference between trust and churn.

Disclaimer: I work for Cloudflare. The views and opinions expressed in this post are my own and do not necessarily reflect the official policy or position of Cloudflare.

This blog discusses the current progress and implementation of an automated ABI compliance reporting system for PostgreSQL, which is also my GSoC 2025 project.

PostgreSQL community conferences, as many other industry driven events, usually do not have proceedings or anything similar. All you get is a slide deck and, if you're lucky, a video recording. But it often feels not enough, as it was with one of my talks last year at PGConfDE, where the topic I was talking about included examples of mathematical modeling to predict how the database will behave. Plenty of things were not said or were not communicated with enough details, because they were simply not fitting the format.

Lately, it feels like every time I go to a technical conference, someone is talking about how great PostgreSQL is. I’d think it’s just me noticing, but the rankings and surveys say otherwise. PostgreSQL is simply very popular. From old-school bare metal setups to VMs, containers, and fully managed cloud databases, PostgreSQL keeps gaining ground. And […]

PostgreSQL Person of the Week Interview with Samed YILDIRIM: I’m originally from Turkey. The last city I lived in Turkey was Istanbul. I am now living in Riga, Latvia for more than 5 years already.

Housekeeping announcements:

this website's PostgreSQL installation is now on version 17 ( insert champagne emoji here ) the search function now works properly with non-ASCII characters ( there was an embarrassing oversight which went unnoticed until someone kindly pointed it out ) PostgreSQL 18 changes this week

This week there have been a couple of renamings:

The basic promise of a query optimizer is that it picks the “optimal” query plan. But there’s a catch - the plan selection relies on cost estimates, calculated from selectivity estimates and cost of basic resources (I/O, CPU, …). So the question is, how often do we actually pick the “fastest” plan? And the truth is we actually make mistakes quite often.