~postgresweekly | Issue 581 - 7+ million Postgres tables without flinching (8)

pg_worker_pool: Extension to Create a Pool of Background Workers — A simple extension that leans on Postgres’s background worker process mechanism to make it easy to distribute queries across a number of workers.

Electric: A Postgres Sync Engine, Now in Beta — It’s always nice to see a new project we casually mentioned a year ago come to fruition, and this real-time engine for syncing data between Postgres and numerous other services (over HTTP) has come a long way since then. GitHub repo.

Running Durable Workflows in Postgres using DBOS — A look at DBOS, a ‘durable workflow’ engine built by a team including none other than one of the founders of the Postgres project.

▶  7+ Million Postgres Tables — Firmly in the space of “you might not wanna do this, but it’s certainly interesting”, an engineer shares an interesting approach to large scale analytics that involves creating a colossal amount of tables (which Postgres has no problem with).

🤯 Explaining the ABI Breakage in Postgres 17.1 — A few weeks ago, Postgres 17.1 was released and some changes caused problems for a few popular extensions. Postgres 17.2 was rapidly released to resolve the problem, but here we get a bit more of the story and technical detail behind what happened. Certainly stuff to be aware of if you’re an extension developer.

Smarter Postgres LLM with Retrieval Augmented Generation — A quick, easy to digest introduction to the concept of ‘RAG’ where the results from large language models are improved by providing added context sourced from extra data sources.

pgBadger 13.0: A Postgres Log Analysis Tool — A performance-focused log analyzer that produces detailed usage reports. Here’s an example report to get a feel for it. GitHub repo.

Building AI Apps on Postgres? Start with pgai — pgai is a PostgreSQL extension that brings more AI workflows to PostgreSQL, like embedding creation and model completion. pgai empowers developers with AI superpowers, making it easier to build search and retrieval-augmented generation (RAG) applications.