# orderedItems[].object.content
PostgreSQL at scale 🔐☸️ Zero-downtime upgrades (Anton Borisov, 10:15), IoT data pipelines with TimescaleDB (Michal Bartak, 11:10), cloud-native Postgres observability & containers (Peter Zaitsev, 15:35), and fuzzing libpq & PgBouncer for security (Adam Wolk, 16:30).

#PostgreSQL #PGDay #PPDD

# orderedItems[].object.content
ChatGPT na PostgreSQL – jak zbudować bazę dla 800 mln użytkowników?

Czy naprawdę trzeba budować własną bazę planetarną, żeby obsłużyć 800 milionów użytkowników? A może wystarczy „nudny” Postgres, trochę dyscypliny i kilka sprytnych sztuczek.

Czytaj dalej:
https://pressmind.org/chatgpt-na-postg resql-jak-zbudowac-baze-dla-800-mln-uzytkownikow/

#PressMindLabs #azure #chatgpt #mvcc #openai #postgresql

# orderedItems[].object.attachment[].name
Futurystyczne centrum danych z serwerami i bazami danych w neonowych kolorach.

# orderedItems[].object.ephemeral.metadata[].twitterTitle
ChatGPT na PostgreSQL - jak zbudować bazę dla 800 mln użytkowników? | PressMind Labs

# orderedItems[].object.ephemeral.metadata[].description
Czy naprawdę trzeba budować własną bazę planetarną, żeby obsłużyć 800 milionów użytkowników? A może wystarczy „nudny” Postgres, trochę dyscypliny i kilka sprytnych sztuczek.

# orderedItems[].object.ephemeral.metadata[].ogDescription
Czy naprawdę trzeba budować własną bazę planetarną, żeby obsłużyć 800 milionów użytkowników? A może wystarczy „nudny” Postgres, trochę dyscypliny i kilka sprytnych sztuczek.

# orderedItems[].object.ephemeral.metadata[].ogTitle
ChatGPT na PostgreSQL - jak zbudować bazę dla 800 mln użytkowników? | PressMind Labs

# orderedItems[].object.ephemeral.metadata[].ogSiteName
PressMind Labs: AI, technologie i przyszłość cyfrowego świata

# orderedItems[].object.ephemeral.metadata[].twitterDescription
Czy naprawdę trzeba budować własną bazę planetarną, żeby obsłużyć 800 milionów użytkowników? A może wystarczy „nudny” Postgres, trochę dyscypliny i kilka sprytnych sztuczek.

# orderedItems[].object.content
https://openai.com/index/scaling-postg resql/ ← in which our #OpEnAi brainiacs tell us that the best way to scale #postgresql is to...not scale it, and just replace it with subscription services. Lol.

# orderedItems[].object.attachment[].name
Simpsons GIF: two beatnik-looking characters at a table in front of a bookshelf shake their heads and say "We've tried nothing, and we're all out of ideas."

# orderedItems[].object.ephemeral.metadata[].twitterTitle
Scaling PostgreSQL to power 800 million ChatGPT users

# orderedItems[].object.ephemeral.metadata[].description
An inside look at how OpenAI scaled PostgreSQL to millions of queries per second using replicas, caching, rate limiting, and workload isolation.

# orderedItems[].object.ephemeral.metadata[].ogDescription
By Bohan Zhang, Member of the Technical Staff

# orderedItems[].object.ephemeral.metadata[].ogTitle
Scaling PostgreSQL to power 800 million ChatGPT users

# orderedItems[].object.ephemeral.metadata[].twitterDescription
By Bohan Zhang, Member of the Technical Staff

# orderedItems[].object.content
#OpenAI hat einen Blogpost veröffentlicht, der sich als technische Doku tarnt, aber eigentlich eine Liebeserklärung ist. An #PostgreSQL, das jetzt 800 Millionen ChatGPT-Nutzer bedient: https://openai.com/index/scaling-postg resql/

Das Rezept: Eine Primärinstanz, 50 Replicas weltweit, PgBouncer davor, Cache-Locking daneben, Rate-Limiting darüber. Und das strikte Verbot, neue Tabellen anzulegen. Schreiblast? Läuft auf CosmosDB. Schema-Änderungen? Fünf Sekunden, dann Abbruch.

Mit genug Cloud-Budget und direktem Draht zum Azure-Team kann man also erstaunlich weit kommen, bevor man alles neu bauen muss. Das ist dann aber weniger ein PostgreSQL-Erfolg als vielmehr die Wahrheit über gewachsene Architekturen: Manchmal ist Weiterbauen billiger als Neudenken.

# orderedItems[].object.ephemeral.metadata[].twitterTitle
Scaling PostgreSQL to power 800 million ChatGPT users

# orderedItems[].object.ephemeral.metadata[].description
An inside look at how OpenAI scaled PostgreSQL to millions of queries per second using replicas, caching, rate limiting, and workload isolation.

# orderedItems[].object.ephemeral.metadata[].ogDescription
By Bohan Zhang, Member of the Technical Staff

# orderedItems[].object.ephemeral.metadata[].ogTitle
Scaling PostgreSQL to power 800 million ChatGPT users

# orderedItems[].object.ephemeral.metadata[].twitterDescription
By Bohan Zhang, Member of the Technical Staff

# orderedItems[].object.content
Next week (1/29 @ 1 PM ET) join our free webinar to learn all about #PostgreSQL 18 features, like...

👉 the new asynchronous I/O subsystem delivering up to 3x performance improvements (& how to set it up)

👉 skip scan for efficient use of indexes even when leading columns are omitted (great for analytics workloads!)

👉 generated column replication for replicating calculated values across distributed architectures

Join us live: https://us02web.zoom.us/webinar/regist er/WN_0235AXQERaybzWCKYHaovQ#/registration

#programming #devops #database #postgres

# orderedItems[].object.ephemeral.metadata[].description
Join us for a comprehensive exploration of PostgreSQL 18's most impactful features transforming database performance and developer workflows.

Asynchronous I/O: Discover the new AIO subsystem delivering up to 3x performance improvements. Learn to configure io_method options (sync, worker, io_uring) for optimal I/O performance.

Skip Scan: Explore the breakthrough that eliminates the "left-most column" limitation for multicolumn B-tree indexes. Queries can now efficiently use indexes even when leading columns are omitted—a game-changer for analytics workloads.

RETURNING Enhancements: Master OLD and NEW aliases for tracking before-and-after values in a single operation. See practical examples of building audit trails without triggers and sophisticated MERGE RETURNING workflows.

Generated Column Replication: Learn about the new publish_generated_columns parameter for replicating calculated values across distributed architectures, plus enhanced conflict monitoring with pg_stat_subscription_stats.

Key Takeaways:

- Configure AIO for maximum performance gains
- Consolidate indexes and accelerate queries with skip scan
- Implement atomic change tracking with RETURNING
- Enable generated column replication in distributed systems

Don't miss this opportunity to gain practical, hands-on knowledge from real-world examples and expert insights. Whether you're planning your PostgreSQL 18 upgrade or exploring its capabilities, this session will equip you with the skills to immediately apply these powerful features in your environment. 

Register now to secure your spot!

# orderedItems[].object.ephemeral.metadata[].ogDescription
Join us for a comprehensive exploration of PostgreSQL 18's most impactful features transforming database performance and developer workflows.

Asynchronous I/O: Discover the new AIO subsystem delivering up to 3x performance improvements. Learn to configure io_method options (sync, worker, io_uring) for optimal I/O performance.

Skip Scan: Explore the breakthrough that eliminates the "left-most column" limitation for multicolumn B-tree indexes. Queries can now efficiently use indexes even when leading columns are omitted—a game-changer for analytics workloads.

RETURNING Enhancements: Master OLD and NEW aliases for tracking before-and-after values in a single operation. See practical examples of building audit trails without triggers and sophisticated MERGE RETURNING workflows.

Generated Column Replication: Learn about the new publish_generated_columns parameter for replicating calculated values across distributed architectures, plus enhanced conflict monitoring with pg_stat_subscription_stats.

Key Takeaways:

- Configure AIO for maximum performance gains
- Consolidate indexes and accelerate queries with skip scan
- Implement atomic change tracking with RETURNING
- Enable generated column replication in distributed systems

Don't miss this opportunity to gain practical, hands-on knowledge from real-world examples and expert insights. Whether you're planning your PostgreSQL 18 upgrade or exploring its capabilities, this session will equip you with the skills to immediately apply these powerful features in your environment. 

Register now to secure your spot!

# orderedItems[].object.ephemeral.metadata[].ogTitle
Welcome! You are invited to join a webinar: PostgreSQL 18 Deep Dive: Performance, Indexing, and Replication Enhancements. After registering, you will receive a confirmation email about joining the webinar.

# orderedItems[].object.content
New entry in #PostgreSQL Event Calendar:

👫 Meetup Toulouse PUG

Date: 2026-04-07T17:00:00Z - 2026-04-07T19:30:00Z
Location: Pictarine, 46 Rue Marco Polo, 31670 Labège, France

ICS file: https://ics.postgresql.life/4gk1rhuppf u26dvfst26fd9nvb.ics

# orderedItems[].object.content
Once won’t hurt — I did a silly benchmark with a clickbait headline 🤣:

#PostgreSQL is faster when replacing SQL tables with MongoDB collections https://dev.to/franckpachot/pgbench-on-mongodb-via-foreign-data-wrapper-i5j

# orderedItems[].object.ephemeral.metadata[].twitterTitle
PgBench on MongoDB via Foreign Data Wrapper

# orderedItems[].object.ephemeral.metadata[].description
Disclaimer: This is an experiment, not a benchmark, and not an architectural recommendation.... Tagged with mongodb, document, database, postgres.

# orderedItems[].object.ephemeral.metadata[].ogDescription
Disclaimer: This is an experiment, not a benchmark, and not an architectural recommendation....

# orderedItems[].object.ephemeral.metadata[].ogTitle
PgBench on MongoDB via Foreign Data Wrapper

# orderedItems[].object.ephemeral.metadata[].twitterDescription
Disclaimer: This is an experiment, not a benchmark, and not an architectural recommendation....

# orderedItems[].object.content
4 causes of table bloat in #PostgreSQL and how to address them https://dev.to/shinyakato_/4-causes-of-table-bloat-in-postgresql-and-how-to-address-them-3ec9

# orderedItems[].object.ephemeral.metadata[].twitterTitle
4 causes of table bloat in PostgreSQL and how to address them

# orderedItems[].object.ephemeral.metadata[].description
What Is Table Bloat?   Table bloat in PostgreSQL refers to the phenomenon where "dead... Tagged with postgres.

# orderedItems[].object.ephemeral.metadata[].ogDescription
What Is Table Bloat?   Table bloat in PostgreSQL refers to the phenomenon where "dead...

# orderedItems[].object.ephemeral.metadata[].ogTitle
4 causes of table bloat in PostgreSQL and how to address them

# orderedItems[].object.ephemeral.metadata[].twitterDescription
What Is Table Bloat?   Table bloat in PostgreSQL refers to the phenomenon where "dead...

# orderedItems[].object.content
📰 Deep Dive: Mastering Supabase and PostgreSQL Architecture in 2026

Explore the 2026 landscape of serverless PostgreSQL. Master Supabase Realtime, Edge Functions, and PG17 migrations to build high-performance, secure apps.

#database #postgresql #supabase #news

🌍 Also in: 🇪🇸 🇫🇷 🇩🇪 🇧🇷 🇮🇹

🔗 https://dataformathub.com/blog/deep-di ve-mastering-supabase-and-postgresql-architecture-in-2026-7tl?utm_source=mastodon&utm_medium=social&utm_campaign=blog

# orderedItems[].object.ephemeral.metadata[].twitterTitle
Deep Dive: Mastering Supabase and PostgreSQL Architecture in 2026

# orderedItems[].object.ephemeral.metadata[].description
Explore the 2026 landscape of serverless PostgreSQL. Master Supabase Realtime, Edge Functions, and PG17 migrations to build high-performance, secure apps.

# orderedItems[].object.ephemeral.metadata[].ogDescription
Explore the 2026 landscape of serverless PostgreSQL. Master Supabase Realtime, Edge Functions, and PG17 migrations to build high-performance, secure apps.

# orderedItems[].object.ephemeral.metadata[].ogTitle
Deep Dive: Mastering Supabase and PostgreSQL Architecture in 2026

# orderedItems[].object.ephemeral.metadata[].twitterDescription
Explore the 2026 landscape of serverless PostgreSQL. Master Supabase Realtime, Edge Functions, and PG17 migrations to build high-performance, secure apps.

# orderedItems[].object.content
[Blog] Spatial Data with PostGIS in PostgreSQL: https://www. sqlpassion.at/archive/2026/01/26/spatial-data-with-postgis-in-postgresql/ #postgres #PostgreSQL #gis #PostGIS

# orderedItems[].object.content
Can't wait to participate in PgDay Boston? Early bird registration is now open through April 17th! We look forward to seeing you in Boston on June 9th!

https://2026.pgdayboston.org/registrat ion/

#PostgreSQL #postgres #conference

# orderedItems[].object.content
pgedge-loadgen: open-source CLI tool to generate realistic PostgreSQL workloads 📈

Use it to:
👉 create schemas for fictional applications
👉 populate them with test data
👉 run load simulations with temporal usage patterns

🔗 Check it out on GitHub: https://github.com/pgEdge/pgedge-loadg en

📖 Read more about it on our blog: https://www. pgedge.com/blog/introducing-pg edge-load-generator-realistic-postgresql-workload-simulation

#programming #devops #database #postgresql #postgres #opensource #dataengineering #sre #sysadmin

# orderedItems[].object.ephemeral.metadata[].twitterTitle
GitHub - pgEdge/pgedge-loadgen: A load generator for PostgreSQL

# orderedItems[].object.ephemeral.metadata[].description
A load generator for PostgreSQL. Contribute to pgEdge/pgedge-loadgen development by creating an account on GitHub.

# orderedItems[].object.ephemeral.metadata[].ogDescription
A load generator for PostgreSQL. Contribute to pgEdge/pgedge-loadgen development by creating an account on GitHub.

# orderedItems[].object.ephemeral.metadata[].ogTitle
GitHub - pgEdge/pgedge-loadgen: A load generator for PostgreSQL

# orderedItems[].object.ephemeral.metadata[].twitterDescription
A load generator for PostgreSQL. Contribute to pgEdge/pgedge-loadgen development by creating an account on GitHub.

# orderedItems[].object.ephemeral.metadata[].description
Anyone who has worked with PostgreSQL in production environments knows that testing database performance is rarely straightforward. Synthetic benchmarks like pgbench are useful for stress testing, but they don't reflect how real applications behave. Production workloads have peaks and troughs, complex query patterns, and user behaviour that varies throughout the day. This is why I'm pleased to introduce the pgEdge Load Generator.

# orderedItems[].object.content
Join us on Tuesday, February 10th at Noon PST for "The 5 levels of Using JSON_Tables” with Jay Miller! RSVP today!

https://www. meetup.com/postgresql-1/events/312977062/?eventOrigin=group_events_list

@PostgreSQL #PostgreSQL #postgres #meetup

# orderedItems[].object.ephemeral.metadata[].description
Join us virtually on Tuesday, Februaru 10th for "The 5 levels of Using JSON_Tables" with Jay Miller.

When JSON_TABLES released I thought this would be the greatest thing e

# orderedItems[].object.ephemeral.metadata[].ogDescription
Join us virtually on Tuesday, Februaru 10th for "The 5 levels of Using JSON_Tables" with Jay Miller.

When JSON_TABLES released I thought this would be the greatest thing e

# orderedItems[].object.ephemeral.metadata[].ogTitle
"The 5 levels of Using JSON_Tables" with Jay Miller, Tue, Feb 10, 2026, 12:00 PM   | Meetup

# orderedItems[].object.ephemeral.metadata[].twitterDescription
Join us virtually on Tuesday, Februaru 10th for "The 5 levels of Using JSON_Tables" with Jay Miller.

When JSON_TABLES released I thought this would be the greatest thing e

# orderedItems[].object.content
Check out the SQL talks at #P2D2 🧠 From PgQ queues (Alexander Kukushkin, 9:20) and what Postgres is still missing (Bruce Momjian, 10:15) to ORMs vs SQL (Petr Šmejkal, 11:10), constraints in PG18 (Gulcin Yildirim Jelinek, 14:15) and SQL regression testing (Radim Marek, 16:30).

#PostgreSQL #PPDD #SQL

# orderedItems[].object.content
There are many use cases for both RAG and MCP servers - but there are significant differences in how your data is accessed & protected depending on your choice.

Our vice president of engineering (Dave Page) wrote a thorough guide on which to choose and when - if you missed it before, here's the link:

🔗 https://www. pgedge.com/blog/rag-servers-vs-mcp-servers-choosing-the-right-approach-for-ai-powered-database-access

#programming #rag #mcp #datasecurity #cybersecurity #dataprotection #opensource #postgresql #postgres #database #aidevelopment #appdev

# orderedItems[].object.ephemeral.metadata[].description
As AI capabilities continue to evolve and integrate more deeply into our applications, we’re faced with interesting architectural decisions about how to expose our data to large language models (LLMs). Two approaches that have gained significant traction are Retrieval Augmented Generation (RAG) servers (such as pgEdge RAG Server) and Model Context Protocol (MCP) servers (such as pgEdge Natural Language Agent). Both have their place, but they serve quite different purposes and come with vastly different security implications – particularly when it comes to database access.

# orderedItems[].object.content
OpenAI team shares their history on scaling #PostgreSQL to 800 million users:

https://openai.com/index/scaling-postg resql/

# orderedItems[].object.ephemeral.metadata[].twitterTitle
Scaling PostgreSQL to power 800 million ChatGPT users

# orderedItems[].object.ephemeral.metadata[].description
An inside look at how OpenAI scaled PostgreSQL to millions of queries per second using replicas, caching, rate limiting, and workload isolation.

# orderedItems[].object.ephemeral.metadata[].ogDescription
By Bohan Zhang, Member of the Technical Staff

# orderedItems[].object.ephemeral.metadata[].ogTitle
Scaling PostgreSQL to power 800 million ChatGPT users

# orderedItems[].object.ephemeral.metadata[].twitterDescription
By Bohan Zhang, Member of the Technical Staff

# orderedItems[].object.content
RE: https://mastodon.social/@fosdempgday/1 15933923088950301

#pgBackRest is one of those tools that keeps surprising me, even after years of working with #PostgreSQL 🐘 Solid, flexible, and once you really get it, it completely changes how confident you feel about backups 🔒

If you’re around next week, come join us in #Brussels for #FOSDEMPGDay 🇧🇪

And if you can’t make it, pgBackRest is part of our next training level at @dataegret, where we share the patterns, gotchas, and real-world lessons we’ve learned along the way 👀
https://dataegret.com/courses-postgres ql-backups-replication-dba3/

# orderedItems[].object.ephemeral.metadata[].description
Attached: 1 image

Meet the #FOSDEMPgDay 2026 Speakers: Stefan Fercot at Data Egret will be speaking on the topic pgBackrest magic you'll wish you knew sooner. Learn more at https://www.postgresql.eu/events/fosdem2026/schedule/session/7324-pgbackrest-magic-youll-wish-you-knew-sooner/ and register at https://2026.fosdempgday.org/registration/

#postgres

# orderedItems[].object.ephemeral.metadata[].ogDescription
Attached: 1 image

Meet the #FOSDEMPgDay 2026 Speakers: Stefan Fercot at Data Egret will be speaking on the topic pgBackrest magic you'll wish you knew sooner. Learn more at https://www.postgresql.eu/events/fosdem2026/schedule/session/7324-pgbackrest-magic-youll-wish-you-knew-sooner/ and register at https://2026.fosdempgday.org/registration/

#postgres

# orderedItems[].object.ephemeral.metadata[].description
Advanced course for experienced DBA who want to deepen their expertise in data protection, replication, and high availability strategies.

# orderedItems[].object.ephemeral.metadata[].ogDescription
Advanced course for experienced DBA who want to deepen their expertise in data protection, replication, and high availability strategies.

# orderedItems[].object.ephemeral.metadata[].ogTitle
PostgreSQL Backups and Replication (DBA3) - Data Egret

# orderedItems[].object.content
OpenAI tackled the challenge of serving 800M users by re‑architecting its PostgreSQL stack: aggressive connection pooling, Azure read replicas, and low‑latency query tuning. The result? Faster ChatGPT responses and a more resilient backend. Curious how they did it? Dive into the scaling playbook. #PostgreSQL #OpenAI #ChatGPT #DatabaseScaling

🔗 https://aidailypost.com/news/openai-sc ales-postgresql-support-800-million-users-through

# orderedItems[].object.ephemeral.metadata[].twitterTitle
OpenAI Scales PostgreSQL for 800M User Surge

# orderedItems[].object.ephemeral.metadata[].description
OpenAI engineers reveal how they scaled PostgreSQL to support 800 million users through strategic database optimization and intelligent query tuning.

# orderedItems[].object.ephemeral.metadata[].ogDescription
OpenAI engineers reveal how they scaled PostgreSQL to support 800 million users through strategic database optimization and intelligent query tuning.

# orderedItems[].object.ephemeral.metadata[].ogTitle
OpenAI Scales PostgreSQL for 800M User Surge

# orderedItems[].object.ephemeral.metadata[].twitterDescription
OpenAI engineers reveal how they scaled PostgreSQL to support 800 million users through strategic database optimization and intelligent query tuning.

# orderedItems[].object.content
⚡ Call for Lightning Talks – Prague Postgres Developers Day 2026!

Got a cool idea, extension, tip, or Postgres story? Share it in 5 minutes. No demos, just sharp slides. Apply now and take the stage on Jan 28! 🚀 https://lnkd.in/dyxtkAx4

#PostgreSQL #PPDD #LightningTalks #PGCommunity

# orderedItems[].object.content
The schedule for pgDay Paris 2026 has been published! Earlybird tickets are still available!

#pgDay #Paris #PostgreSQL #Conference

https://2026.pgday.paris/schedule/