Neues vom PostgreSQL Planet

This is the third post about running Jepsen against CloudNativePG. Earlier posts:

Let's talk about relation-level locks and various confusions, surprises and what is worth to remember in practice.

The key page in Postgres docs describing relation-level locks is here: https://www.postgresql.org/docs/current/explicit-locking.html#LOCKING-TABLES

Many experienced DBAs joke that you can boil down the entire job to a single rule of thumb: Don’t lose your data. It’s simple, memorable, and absolutely true – albeit a little oversimplified.

Mark Porter’s Cultural Hint “The Onion of our Requirements” conveys the same idea with a lot more accuracy:

To warm up, let's talk about lightweight and heavyweight locks (or "regular locks" or just "locks").

I'm using these materials:

Moving a Postgres database isn’t a small task. Typically for Postgres users this is one of the biggest projects you’ll undertake. If you’re migrating for a new Postgres major version or moving to an entirely new platform or host, you have a couple options:

PostgreSQL handles large JSON payloads reasonably well until you start updating or deleting them frequently. Once payloads cross the 8 KB TOAST threshold and churn becomes high, autovacuum can dominate your I/O budget and cause other issues. I have been exploring the idea of moving older JSON data (read: cold data) to Parquet on S3 while keeping recent data hot in PostgreSQL daily partitions, then simply dropping those partitions instead of running expensive DELETE operations and subsequent vacuum cycles.

PostgreSQL is a very versatile database. It has countless ways of bringing different functionalities to an already very sophisticated piece of software. Today, I’m going to show you how to use Rust and pgrx to bring etcd into your PostgreSQL database through a nice little interface called Foreign Data Wrappers.

(an image representing rust, etcd and postgres working together. Drawn by Jeremy Sztavinovszki)

Our platform team has a regular meeting where we often use ops issues as a springboard to dig into Postgres internals. Great meeting today – we ended up talking about the internal architecture of Postgres replication. Sharing a few high-quality links from our discussion:

Alexander Kukushkin’s conference talk earlier this year, which includes a great explanation of how replication works

On 29th of September 2025, Tom Lane committed patch: Add GROUP BY ALL.   GROUP BY ALL is a form of GROUP BY that adds any TargetExpr that does not contain an aggregate or window function into the groupClause of the query, making it exactly equivalent to specifying those same expressions in an explicit GROUP … Continue reading "Waiting for PostgreSQL 19 – Add GROUP BY ALL."

the psql client version 18 comes with pipelining, which can speed up client-server communication. In this post, let's see how it works and how much can be gained in query throughput with a simple example.

 Learning Structured Query Language can be frustrating when double-checking that what you wanted to have done is actually what was done. PostgreSQL 18 has 'OLD and NEW support for RETURNING clauses in INSERT, UPDATE, DELETE, and MERGE commands'. Now you can get instant feedback. 

The addition of the RETURNING clause in the previous version made MERGE much easier to use. Now it makes other commands easier.

To demonstrate, let's create a table with one column that is designated as a unique, primary key integer and insert a value.

© Laurenz Albe 2025

If you are reading this hoping that PostgreSQL finally got UPDATE ... LIMIT like MySQL, I have to disappoint you. The LIMIT clause is not yet supported for DML statements in PostgreSQL. If you want to UPDATE only a limited number of rows, you have to use workarounds. This article will describe how to do this and how to avoid the pitfalls and race condition you may encounter. Note that most of the following also applies to DELETE ... LIMIT!