Neues vom PostgreSQL Planet

PostgreSQL maintenance doesn't have to mean downtime anymore. With pgEdge's zero-downtime node addition, you can perform critical maintenance tasks like version upgrades, hardware replacements, and cluster expansions without interrupting production workloads. Your applications stay online. Your users stay connected.

There is common misconception that troubles most developers using PostgreSQL: tune VACUUM or run VACUUM, and your database will stay healthy. Dead tuples will get cleaned up. Transaction IDs recycled. Space reclaimed. Your database will live happily ever after.

But there are couple of dirty "secrets" people are not aware of. First of them being VACUUM is lying to you about your indexes.

While moving production database workloads towards cloud-native (Kubernetes) environments has become very popular lately, plenty of users still rely on good old Docker containers. Compared to running PostgreSQL on bare metal, on virtual machines, or via a Kubernetes operator, Docker adds a bit of complexity, especially once you want to go beyond simple pg_dump / pg_restore for backups, upgrades, and disaster recovery.

In a recent Postgres patch authored by Greg Sabino Mullane, Postgres has a new step forward for data integrity: data checksums are now enabled by default.

This appears in the release notes as a fairly minor change but it significantly boosts the defense against one of the sneakiest problems in data management - silent data corruption.

Let’s dive into what this feature is, what the new default means for you, and how it impacts upgrades.

Postgres Ibiza (PGIBZ): An open source conference designed to bring together people with a love for PostgreSQL in Ibiza, a relaxed place for fresh and innovative discussions. An international event run by the nonprofit PostgreSQL España.

This was the first time that the Data Bene team attended the event, and we’re happy to share that it was a very positive experience.

Postgres Ibiza (PGIBZ): An open source conference designed to bring together people with a love for PostgreSQL in Ibiza, a relaxed place for fresh and innovative discussions. An international event run by the nonprofit PostgreSQL España.

This was the first time that the Data Bene team attended the event, and we’re happy to share that it was a very positive experience.

The ClickHouse blog has a posted a piece by yours truly introducing pg_clickhouse, a PostgreSQL extension to run ClickHouse queries from PostgreSQL:

In this blog, we explore Postgres constraints through the pg_constraint catalog, covering table vs. column constraints, constraint triggers, domains and more.

In Part 1 we loaded our documentation into PostgreSQL. In Part 2 we chunked those documents and generated vector embeddings. Now it's time to put it all together with an API that your applications can use.

If you need to transition easily from Oracle to PostgreSQL without worrying about type conversions or other Oracle packages that require modifications to be PostgreSQL-compatible, a useful solution is IvorySQL!

There’s nothing simple about simplification! It is very common to want to slim down the size of geometries, and there are lots of different approaches to the problem.

We will explore different methods starting with ST_Letters for this rendering of the letter “a”.

PostgreSQL is highly suitable for powering critical applications in all industries. However, to run critical applications, there are key requirements which are absolutely needed: High-Availability and automatic failover. 

This document explains which options are available and which problems one can solve with PostgreSQL. We have listed the most common setups and some of the most common recommendations. 

In Part 1 of this series, we loaded our documentation into PostgreSQL using the pgEdge Document Loader. Our documents are sitting in the database as clean Markdown content, ready for the next step: turning them into something an LLM can search through semantically.In this post, we'll use pgEdge Vectorizer to chunk those documents and generate vector embeddings.

If you've ever had to scrub significantly large tables—whether updating older records or deleting expired ones—you know the pain of trying to do it efficiently without locking the entire table. One common trick is to iterate over the ctid (the physical location of the tuple) to process the table in chunks. Until now, this was strictly a single-threaded affair. But with the latest commit to

On Nov. 20, the day after GIS Day, Elizabeth Christensen and I hosted the 7th annual PostGIS Day, a celebration of the Little Spatial Database That Could. Brought to you this year by Snowflake, the event featured an amazing collection of speakers from around the globe — from India to Africa, Europe to North America.

Last week, I read The Register’s coverage of MongoDB CEO Chirantan “CJ” Desai telling analysts that a “super-high growth AI company … switched from PostgreSQL to MongoDB because PostgreSQL could not just scale.” (The Register)

I believe you can show the value of your own technology without tearing down another. That is really what this post is about.

PGUG.EE met on December 3 2025 in Estonia, organized by Kaarel Moppel & Ervin Weber

Talks

• Mayuresh Bagayatkar
• Alexander Matrunich
• Ants Aasma
• Kaarel Moppel

Bruce Momjian spoke at the PG Armenia Community Meetup, organised by Emma Saroyan on December 4 2025.

If you need to migrate quickly from Oracle to PostgreSQL without worrying about type conversions or other Oracle packages that require modifications to be PostgreSQL-compatible, a useful solution is IvorySQL!

I have attended over one hundred Postgres meetups over the years. The usual format is: food with individual discussion, lecture with group questions, and finally more individual discussion. I just spoke at an Armenia PostgreSQL User Group meetup and the event organizer Emma Saroyan did something different — she did a group mobile phone quiz after my lecture.

In the past there have been many discussions about using UUID as a primary key in PostgreSQL. For some applications, even a BIGINT column does not have sufficient range: it is a signed 8‑byte integer with range −9,223,372,036,854,775,808 to +9,223,372,036,854,775,807. Although these values look big enough, if we think about web services that collect billions or more records daily, this number becomes less impressive.