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While working on SQL/PGQ patch I wanted to find an equality operator for given left and right argument types to construct a condition to match an edge with its adjacent vertexes. It would look as simple as calling C function oper() with operator as "=" and required left and right data types. But soon it turned out to be a walk in PostgreSQL's operator labyrinth, which held my equality operator at the center instead of Minotaur.

vip-manager has long been a crucial tool for managing virtual IPs in PostgreSQL HA setups, providing reliable leader routing. With the release of version 2.8.0, we're taking things to the next level by introducing native integration with the Patroni REST API.

pgBackRest is a popular backup and restore tool for PostgreSQL, known for easily handling even the largest databases and workloads. It’s packed with powerful features, but all that flexibility can sometimes feel a bit overwhelming.

In late November, on the day after GIS Day, we hosted the annual PostGIS day online event. 22 speakers from around the world, in an agenda that ran from mid-afternoon in Europe to mid-afternoon on the Pacific coast.

Rails developers know the joy of working with ActiveRecord. DHH didn’t just give us a framework; he gave us a philosophy, an intuitive way to manage data that feels delightful. But when it comes to time-series data, think metrics, logs, or events, ActiveRecord can start to feel a little stretched. Handling huge volumes of time-stamped data efficiently for analytics? That’s a challenge it wasn’t designed to solve (and neither was PostgreSQL).

Rails developers know the joy of working with ActiveRecord. DHH didn’t just give us a framework; he gave us a philosophy, an intuitive way to manage data that feels delightful. But when it comes to time-series data, think metrics, logs, or events, ActiveRecord can start to feel a little stretched. Handling huge volumes of time-stamped data efficiently for analytics? That’s a challenge it wasn’t designed to solve (and neither was PostgreSQL).

Rails developers know the joy of working with ActiveRecord. DHH didn’t just give us a framework; he gave us a philosophy, an intuitive way to manage data that feels delightful. But when it comes to time-series data, think metrics, logs, or events, ActiveRecord can start to feel a little stretched. Handling huge volumes of time-stamped data efficiently for analytics? That’s a challenge it wasn’t designed to solve (and neither was PostgreSQL).

I was invited to the Maintainable Podcast hosted by Robby Russell. We talked about what makes software maintainable and naturally we also talked about Postgres.

Efficient data retrieval is crucial in any production environment, especially for databases handling heavy traffic and large datasets. PostgreSQL’s operator classes are a powerful but often overlooked tool for fine-tuning index performance. They allow you to control how PostgreSQL compares data within an index, helping to streamline searches and improve query efficiency in ways that default settings simply can’t match.

• Rushabh Lathia was interviewed as “PostgreSQL Person of the Week”
• Markus Winand updated the modern-sql.com website, it now includes all the PostgreSQL v17 features.
• Gulcin Yildirim Jelinek organized the Prague November Meetup. Tudor Golubenco and Noémi Ványi* spoke.

In a previous article in this series, I explored the magic of INSERT...UNNEST for improving PostgreSQL batch INSERT performance. While it’s a fantastic technique, I know it’s not the fastest option available (although it is very flexible). Originally, I hadn't intended to loop back and benchmark all the batch ingest methods, but I saw a lot of confusion out there, so I'm back, and this time I'm looking at COPY too.

The Postgres open source project is nearly 30 years old, I personally started using it about 20 years ago. And I’ve been contributing code for at least 10 years. But even with all that experience I find it really difficult to make judgments about how the performance changed over the years. Did it improve? And by how much? I decided to do some benchmarks to answer this question.

This year, I traveled to many conferences, such as the PGconf.eu in Athens for example or the P2D2 in Prague. Every conference is a great opportunity to get unique insights and networking possibilities. However, despite its proximity to Austria, I’ve never been able to make it to the DOAG (Deutsche Oracle-Anwendergruppe) conference in recent years. This year, I decided it was finally time to change that!

Upgrades between PostgreSQL major versions are famously annoying. You can’t just install the server binaries and restart, because the format of the data directory is incompatible.

Why is that? Why can’t we just keep the data format compatible?

Perhaps surprisingly, the data format is actually mostly compatible, but not completely. There are just a few things missing that are very hard to solve.

When I work with other relational databases I am reminded about how I can't use my favorite PostgreSQL hacks in them. I call these hacks PostgreSQLisms. A PostgreSQLism is a pattern of SQL unique to PostgreSQL or descendants of PostgreSQL. In this post I'm going to cover some of my favorite ones.

Continue reading "Some of my favorite PostgreSQLisms"

New Blog Post Title: How can I send mail or HTTP request from database? This question happens every now and then in one of PostgreSQL support places. Whenever it happens, I just suggest to not try, as interacting with outside world from database can be problematic, and instead use LISTEN/NOTIFY. But it occurred to me, … Continue reading ""

PostgreSQL users often employ analytical queries that sort and group data by different rules. Optimising these operators can significantly reduce the time and cost of query execution. In this post, I will discuss one such optimisation: choosing the order of columns in the GROUP BY expression.

Several weeks ago, I started a pgsql-hackers thread proposing a new extension file organization and a search path GUC for finding extensions.

In a world where we constantly seek to automate repetitive tasks, it is common to write down a query in a script, make it more convenient, and eventually integrate the whole thing into a project’s codebase. Tools like SQL*Plus and psql can be powerful allies in this game, as relevant as Bash or Python interpreters.

Your database is ticking along nicely - until a simple DELETE brings it to its knees. What went wrong? While we tend to focus on optimizing SELECT and INSERT operations, we often overlook the hidden complexities of DELETE. Yet, removing unnecessary data is just as critical. Outdated or irrelevant data can bloat your database, degrade performance, and make maintenance a nightmare. Worse, retaining some types of data without valid justification might even lead to compliance issues.