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A useful new feature was introduced on 11 December 2025: Allow expiration of the oldest full backup regardless of current retention. Details are available in commit bf2b276.

One of the principal and most powerful components of the pgEdge Agentic AI Toolkit is the pgEdge Postgres MCP Server. In just over a year MCP (Model Context Protocol), initially developed by Anthropic, has become the standard way to connect LLMs to external data sources and tools.

We are delighted today to be announcing the beta release of our pgEdge Agentic AI Toolkit for Postgres.  We’ve had the benefit of collaborating on real-world Postgres-based AI applications the past two years with a number of leading customers, and this product announcement is the outgrowth of this learning.We listened to customers as they refined their AI strategies in response to the rapid evolution of LLMs, Agentic AI and integration technologies such as the Model Context Protocol (MCP), and as we did so a few things sto

© Laurenz Albe 2025

Most major Linux distributions have upgraded to the GNU C library version 2.28 or later. Therefore, there is a growing awareness that an operating system upgrade can lead to index corruption. However, rebuilding all your indexes can slow down the upgrade process considerably. In this article, I want to discuss how you can avoid rebuilding more indexes than necessary.

A Journey Through PostgreSQL Events

• Introduction
• Community recognition (transparency, inclusivity, organisational balance)
• If I organise a PostgreSQL event — does it have to be recognised?
• Are community-recognised events better than those that aren’t?
• Conferences — a quick flyover (pgDays, pgConfs, FOSDEM, PGConf.dev etc.)
• PostgreSQL User Groups / meet-ups
• Key takeaways
• Which PostgreSQL event to attend?

Quick announcement to say that I’ve replaced the ancient markdown parser with a new one, discount, which supports tables, code fences, definition lists, and more. I reindexed pg_clickhouse this morning and it’s sooo nice to see the table properly formatted.

PostgreSQL 17 introduced streaming I/O – grouping multiple page reads into a single system call and using smarter posix_fadvise() hints. That alone gave up to ~30% faster sequential scans in some workloads, but it was still strictly synchronous: each backend process would issue a read and then sit there waiting for the kernel to return data before proceeding. Before PG17, PostgreSQL typically read one 8kB page at a time.

Earlier this year we started a program (“Developer U”) to help colleagues who show promise for PostgreSQL Development to become contributors. Meet: Nishant Sharma, Staff SDE, who maintains a list of places in the world he has yet to visit.

Data privacy regulations such as GDPR, CCPA, and HIPAA have made it increasingly important for organisations to protect personally identifiable information (PII) in their databases. Whether you're creating a development environment from production data, sharing datasets with third parties, or simply trying to minimise risk, you'll often need to anonymise sensitive data whilst maintaining the structure and relationships within your database.I've been working on a tool to address this need: .

On December 11, the PGDay CERN 2026 CfP committee met to finalize the talk selection. The committee members are listed here:

From time to time I see questions from otherwise well informed people about how the PostgreSQL Build farm checks how pg_upgrade checking is done across versions, e.g. how does it check upgrading from release 9.5 to release 18. I realize that this isn't well documented anywhere, so here is a description of the process.

All of the code referenced here can be found at https://github.com/PGBuildFarm/client-code.

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.