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My recommended methodology for performance improvement of PostgreSQL starts with query optimization. The second step is architectural improvements, part of which is the partitioning of large tables.

Partitioning in PostgreSQL is one of those advanced features that can be a powerful performance booster. If your PostgreSQL tables are becoming very large and sluggish, partitioning might be the cure.

The Big Table Problem

Jenn and I headed to Bellingham April 26 & 27th for LinuxFest Northwest, a 100% volunteer-run, free event. This is always a fun conference and there were lots of familiar faces this year! Some stats:Over 100 booth visitorsJust wanted to say how much they love Postgres: 18Asked about migrating from MySQL to Postgres: 1“We love […]

Earlier this year, I had the incredible opportunity to present at PGConf India, where I delved into the intricacies of Write-Ahead Logging (WAL) in PostgreSQL. My presentation aimed to demystify this crucial database feature that ensures data integrity and enhances performance. 

pgroll v0.12 includes usability improvements like verbose mode and idempotent migrate command.

Why Bridge Java with C in the First Place?

Bridging Java and C combines the strengths of both languages. A C application may rely on Java for modern libraries, cloud APIs, or UI and web capabilities, while a Java app might need C for low-level system access or performance-critical tasks. Sometimes, there’s simply no alternative—certain features only exist in one language. While modern languages like C++ and Go offer both high- and low-level control, many systems aren’t written in them.

With the Postgres 18 Beta 1 release this week a multi-year effort, and significant architectural shift in Postgres is taking shape: Asynchronous I/O (AIO). These capabilities are still under active development, but they represent a fundamental change in how Postgres handles I/O, offering the potential for significant performance gains, particularly in cloud environments where latency is often the bottleneck. Why asynchronous I/O matters How Postgres 17’s read streams paved the way New io_method…

In this blog, we're continuing to explore the power of multi-master replication (MMR) with the pgEdge distributed Postgres platform and its open source extension, Spock. In the first Part 1 of this blog topic, we discussed different replication methods and deployment models for PostgreSQL replication.

Before we delve into the main subject of this blog, it is essential to understand the benefits of PostgreSQL replication, and the difference between single-master replication (SMR) and multi-master replication (MMR). In every modern business application, the database is becoming a critical part of the architecture and the demand for making the database performant and highly available is growing tremendously.

Howto guide for upgrading PostgreSQL from version 16 to 17 on Ubuntu, after its upgrade from version 24.10 to 25.04 (Plucky Puffin).

In the PostgreSQL world, as well as in order database systems, data types play a crucial role in ensuring optimal performance, efficiency, as well as semantics. Moreover, some data types are inherently easier and faster to index than others. Many people are not aware of the fact that indexes indeed make a difference, so let us take a look and see how long it takes to index the very same data using different
types.

The last Extension Ecosystem Mini-Summit is upon us. How did that happen?

PostgreSQL 18 changes this week

The PostgreSQL release is slowly taking shape, with the first draft of release notes now available. Corrections and additions can be sent via the pgsql-hackers thread " PG 18 release notes draft committed ".

You know I had to do it as soon as I found it was possible. Yes, I installed and enabled AI in the DBeaver Query Editor so I can use AI with my PostgreSQL database work. Let’s face it. It was inevitable. However, the setup isn’t intuitive. Setting Up in DBeaver I’m going to assume […]

The post AI in the DBeaver Query Editor appeared first on Grant Fritchey.

On 8th of April 2025, Daniel Gustafsson committed patch: Add function to get memory context stats for processes   This adds a function for retrieving memory context statistics and information from backends as well as auxiliary processes. The intended usecase is cluster debugging when under memory pressure or unanticipated memory usage characteristics.

This blog posting is part of a series about organizing Meetups. While mostly centered around PostgreSQL Meetups, large parts can be adapted by other Meetups as well. All postings in this series: Checklist for Meetup Attendees (this posting) Checklist for Meetup Speakers Checklist for Meetup Organizers Overview posting Attending an in-person Meetup You found an interesting Meetup, and like to sign up. Before you sign up, please read the entire Meetup description.

This blog posting is part of a series about organizing Meetups. While mostly centered around PostgreSQL Meetups, large parts can be adapted by other Meetups as well. All postings in this series: Checklist for Meetup Attendees Checklist for Meetup Speakers Checklist for Meetup Organizers (this posting) Overview posting You are organizing a Meetup. Congratulations, this is big! Here are some recommendations: First things first: find a date. Pay attention to school holidays and public holidays, especially for in-person Meetups.

This blog posting is part of a series about organizing Meetups. While mostly centered around PostgreSQL Meetups, large parts can be adapted by other Meetups as well. All postings in this series: Checklist for Meetup Attendees Checklist for Meetup Speakers (this posting) Checklist for Meetup Organizers Overview posting You are speaking at a Meetup. Congratulations! General advice Check your slides for a good contrast, and fonts large enough.

A few days ago, I wrote about a surprising planner behavior with CTEs, DELETE, and LIMIT in PostgreSQL, a piece I hastily put together on a bus ride. That post clearly only scratched the surface of a deeper issue that I’ve since spent way too many hours exploring. So here are some more formed thoughts and findings. The core issue revisited Let’s quickly recap: when using a query like the following, the planner might execute your query in ways you don’t expect.

Greetings!

Fault tolerance is a very important aspect of every non-startup application.
It can be described as a definition:

Fault tolerance is the ability of a system to maintain proper operation despite failures or faults in one or more of its components.

But this gives only slight overview - fault tolerance concerns many areas especially when we are talking about software engineering:

I have just completed the first draft of the Postgres 18 release notes. It includes a little developer community feedback but still needs more XML markup and links.