Quickly implement DB branching in any @PostgreSQL database by installing DBLab SE into your AWS, GCP, Digital Ocean, or Hetzner Cloud account in just a few clicks. Includes lots of extensions, monitoring features, and vendor support: Console.Postgres.ai

PgQue got a website with docs – pgque.dev

Working on this is a lot of fun. Here I shared how it all started, what original PgQ already has and what didn't, and what v0.2 brings (RC1 stamped yesterday)

What a nice blog post by Christophe Pettus PgQue: Two Snapshots and a Diff thebuild.com/blog/2026/05/03…

Precise (not sampled) wait even analysis is something I didn't expect to have for Postgres - but here we go Being able to zoom into concrete millisecond (!) and see the exact chain of wait events opens new possibilities for RCA, benchmarks, and performance studies links 👇

New episode: "pg_wait_tracer" Nik and Michael are joined by Dmitry Fomin to discuss his new tool pg_wait_tracer, as well as changes to core that would allow wait event tracing with lower overhead (and on managed services). 🎧 postgres.fm/episodes/pg_wait… 📺 youtu.be/efY85jwfcQ8

PgQue v0.1.0 is out. PgQ -- the Postgres queue system built at Skype 20 years ago for 1B-user-scale workloads -- repackaged for the managed-Postgres era. One SQL file. No C extension. No external daemon. pg_cron to tick. Why bother reviving a 2007 architecture? Every major Postgres queue in production today uses some flavor of SKIP LOCKED UPDATE/DELETE. It works under light load. When you have more data and higher load, it degrades predictably. Then you get posts like these: - Brandur at Heroku, 2015: 60k job backlog in one hour from a single open transaction - PlanetScale, 2026: death spiral at 800 jobs/sec - River issue #59, awa issue #169 and so on, Oban's partitioning work, PGMQ's autovacuum tuning guide and duct-taping with pg_partman The core issue is how Postgres MVCC is implemented and how we deal with it. Dead tuples in the hot path, xmin horizon pinned, vacuum falling behind, query performance quickly degrades. This happens every time you run pg_dump, execute an analytical query, or have a lagging/unused logical replication slot. PgQ solved this in 2007 with snapshot-based batching and TRUNCATE rotation -- zero dead tuples in the event path, by design. But PgQ needed a C extension and an external daemon. Which means it doesn't run on RDS, Aurora, Cloud SQL, AlloyDB, Supabase, or Neon -- i.e., where most Postgres lives now. PgQue closes that gap. 💎 Pure SQL PL/pgSQL (PgQ engine) 👩‍💻 \i sql/pgque.sql -- you're done 🕑 pg_cron replaces pgqd (optional, recommended) 💻 Python, Go, TypeScript client examples shipped 💙 Apache 2.0 Trade-off: end-to-end event delivery latency is up to a second, it depends on ticking frequency. If you need sub-3ms job dispatch, use River, Oban, or graphile-worker (and avoid anything that blocks xmin horizon). If you need high-throughput event streaming with fan-out inside Postgres -- Kafka-shaped, without Kafka and dealing with transactional outbox implementation -- this is the right shape of tool. Kudos to Marko Kreen and Skype engineers who implemented this decades ago, for the original PgQ, and to Alexander Kukushkin whose recent "Rediscovering PgQ" talk brought this quiet corner of the Postgres ecosystem back into view. Stars, issues, PRs, and honest criticism all welcome. Link 👇

Stop giving your AI agents access to your production database. Here is the setup that fixes it. I was using @neondatabase for disposable Postgres environments. Great DX, branching, one-click resets. Then traffic grew, costs followed, and even dev environments got expensive. Paying for a production-grade managed service just to run experiments started to feel hard to justify. So I went looking for an open source alternative and found @Database_Lab. It takes any Postgres database and lets you spin up isolated clones, branches, and snapshots from it. Reset to any point with one click. Rerun migrations. Break things freely. Zero risk to anything real. The detail that matters most: data flows one direction only. From Postgres into Database Lab, never the other way. Your source database stays completely untouchable. AI agents are getting broader infrastructure access every week. Giving them a safe, isolated clone instead of production access is basic risk management at this point.

PG18 preserves planner statistics on upgrade — even from PG14 postgres.ai/blog/20260324-pg…

For fun, I rewrote psql in Rust and integrated it with AI meet "rpg" -- an experimental CLI maybe, at some point, it will bring ideas to psql itself thoughts? link in the 1st comment

How moving one word can speed up a query 10–50x postgres.ai/blog/20260311-no…

pg_ash v1.3 released -- Active Session History for Postgres, pure SQL. New in 1.3: - pg_cron now optional -- works with external schedulers - set_debug_logging() -- RAISE LOG per sampled session - pgss-dependent functions fail fast with clear errors - Azure Flexible Server compatibility - PG14-18 tested Install: \i sql/ash-install.sql No extensions, no restart. Works on RDS, Cloud SQL, AlloyDB, Supabase, etc.

it was a fun session -- prototyped command tag customization at protocol level: github.com/NikolayS/postgres…