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If you've ever compared database feature matrices, you may have noticed something a bit peculiar. Oracle has Transparent Data Encryption. SQL Server has it. MySQL has it. Even MariaDB has it. But Postgres, which we all consider the best database engine? Conspicuously absent.It’s not that nobody wants TDE. Compliance frameworks like PCI DSS and HIPAA practically demand encryption at rest. Cloud deployments make the “stolen disk” threat model more tangible than ever.

PostgreSQL's default 5-minute checkpoint interval wastes I/O on modern servers.

On 12 May, 2026 the San Francisco Bay Area PostgreSQL Meetup Group met virtually, organized by Katharine Saar, Stacey Haysler and Christophe Pettus. Alex Yarotsky spoke at the event.

The Swiss PGDay Program Committee met to finalize the schedule:

• Marion Baumgartner
• Tobias Bussmann
• Andreas Geppert
• Johannes Graën
• Stefan Keller
• Michelle Willen

Community Blog Post:

A critical integer wraparound bug lets unprivileged SQL users trigger heap corruption with potential arbitrary code execution.

If you've used docs.pgedge.com recently, you've probably met Ellie. Ask her how to set up multi-master replication, or what port the MCP Server listens on, and she pulls the relevant documentation, assembles it into context, and gives you a grounded answer with source citations. She doesn't guess or hallucinate. She finds the actual docs and synthesizes an answer from them.Ellie is a RAG Server deployment.

One Database at a Time, or All at Once?

You have deployed your new cluster. Now comes the work of moving your data and cutting over to it. Reading that sentence, you might assume cutover is something you figure out at the end, after the migration is done. And in practice, that is the order in which things happen. But technically, it is your cutover strategy that decides how you migrate, not the other way around. 

I was reading Markus Winand’s latest post on ORDER BY history last week. If you haven’t read it yet, go read it. Markus is one of the best writers on SQL standards, and this post is no exception. One line stopped me cold. The compatibility table for “expressions on selected columns.” Postgres: partial. PostgreSQL 18: still partial. That itch needed scratching. What the standard says 🔗SQL:1999 lifted a restriction from the original ORDER BY clause.

PostgreSQL validates function bodies at creation time by default, catching syntax errors early.

After helping out a buddy with the job title of Data Analyst, who experienced some light Postgres “bucketing” woes - and given the fact that this was not the first such occasion in that area over the years, though I’d help future googlers / LLM-ers out a bit as well,...

PostgreSQL's Table Access Method API is finally seeing real action.

PostgreSQL's `bytea_output` parameter controls how binary data is formatted when sent to clients: the modern `hex` format (default since 9.0) or the legacy…

#​649 — May 20, 2026

Web Version

Postgres Weekly

PgBouncer 1.25.2 shipped a patch for a pre-authentication crash (CVE-2026-6664). Any TCP connection can take down your pooler. Patch this week.

When the future of pgBackRest suddenly became uncertain, the PostgreSQL ecosystem reacted quickly.

At Percona, we believed the most important question was not:

what replaces it?

but:

how do we ensure pgBackRest remains healthy, sustainable, and open for everyone?

That distinction matters.

In Part 3 of this special “Postgres in Production” deep dive series, Ryan Booz walks through where pg_stat_statements actually stores your query text. Spoiler: it’s not in the in-memory hash table you might expect. He covers the file’s location on disk, how it grows, the pointer mechanism that ties hash table entries back to your SQL, the quirky consequence that the same query text can appear multiple times, and why ORM-heavy workloads can balloon this file to hundreds of megabytes.

PostgreSQL, often through platforms like Supabase, is increasingly becoming part of the default stack for many AI applications. That level of adoption says something important about where engineering teams are placing their trust.

Supabase has become one of the most common starting points for AI products. Most AI frameworks support PostgreSQL and pgvector directly. For many teams, PostgreSQL is already part of the stack before the AI layer is even introduced. 

Events unfolded quickly over the course of a couple of weeks starting on 27 April 2026, when a message appeared on the pgBackRest project announcing: that the repository would be archived and active maintenance would stop.

PostgreSQL's Bonjour parameters let you advertise a server on the local network via Apple's service-discovery protocol—a clever 2002 idea that hasn't aged well.

The conversation around AI infrastructure today is heavily focused on models, GPUs, inference speed, and vector databases. These are important building blocks, but they often distract from a deeper architectural challenge that is beginning to emerge as enterprises move from experimentation toward operational AI systems.

The challenge is memory.

Note: this post was not rewritten by AI

I’ve been saying for a long time that AI can’t help me because no one else codes the way I do, so it doesn’t have any reference points. Then I realized many advantages of having AI perform some boring tasks, like writing tests (we know we need unit tests, and why we are not writing them? because we don’t have time!).