# pgq

Published articles for pgq.

This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles.

## Waiting for PostgreSQL 19 - SQL Property Graph Queries (SQL/PGQ)

DevFeed: [Waiting for PostgreSQL 19 - SQL Property Graph Queries (SQL/PGQ)](<https://devfeed.tech/articles/waiting-for-postgresql-19-sql-property-graph-queries-sql-pgq-33693.md>)

Original publisher: [Read original article](<https://www.depesz.com/2026/07/31/waiting-for-postgresql-19-sql-property-graph-queries-sql-pgq/>)

Author: depesz

Published: 2026-07-31T16:57:44Z

Content type: opinion

Language: en

Sources: [select \* from depesz;](<https://devfeed.tech/sources/select-from-depesz.md>)

Topics: [PostgreSQL](<https://devfeed.tech/topics/postgresql.md>), [SQL](<https://devfeed.tech/topics/sql.md>), [Graphs](<https://devfeed.tech/topics/graphs.md>), [function](<https://devfeed.tech/topics/function.md>), [pattern matching](<https://devfeed.tech/topics/pattern-matching.md>)

Tags: [function](<https://devfeed.tech/tags/function.md>), [graph](<https://devfeed.tech/tags/graph.md>), [graphs](<https://devfeed.tech/tags/graphs.md>), [pattern-matching](<https://devfeed.tech/tags/pattern-matching.md>), [pg19](<https://devfeed.tech/tags/pg19.md>), [pgq](<https://devfeed.tech/tags/pgq.md>), [postgresql](<https://devfeed.tech/tags/postgresql.md>), [property](<https://devfeed.tech/tags/property.md>), [sql](<https://devfeed.tech/tags/sql.md>), [uncategorized](<https://devfeed.tech/tags/uncategorized.md>), [waiting](<https://devfeed.tech/tags/waiting.md>)

### AI overview

The article discusses PostgreSQL's SQL/PGQ implementation for property graph queries, including GRAPH_TABLE, graph pattern matching, and related DDL commands. It notes that the change was later rolled back and expresses the author's uncertainty about the practical benefits and usability of the syntax.

### Source excerpt

Important update This change has been rolled back. Discussion can be found here. On 16th of March 2026, Peter Eisentraut committed patch: SQL Property Graph Queries (SQL/PGQ) Implementation of SQL property graph queries, according to SQL/PGQ standard (ISO/IEC 9075-16:2023). This adds: - GRAPH_TABLE table function for graph pattern matching - DDL commands ... Continue reading "Waiting for PostgreSQL 19 - SQL Property Graph Queries (SQL/PGQ)"

## SFPUG meeting presentation on Skytools 3 replication tools

DevFeed: [SFPUG meeting presentation on Skytools 3 replication tools](<https://devfeed.tech/articles/sfpug-meeting-34662.md>)

Original publisher: [Read original article](<https://tapoueh.org/conf/sfpug-meeting/>)

Published: 2013-07-17T22:00:00Z

Content type: news

Language: en

Sources: [Dimitri Fontaine](<https://devfeed.tech/sources/dimitri-fontaine.md>)

Topics: [Replication](<https://devfeed.tech/topics/replication.md>), [version](<https://devfeed.tech/topics/version.md>), [PostgreSQL](<https://devfeed.tech/topics/postgresql.md>)

Tags: [pgq](<https://devfeed.tech/tags/pgq.md>), [postgresql](<https://devfeed.tech/tags/postgresql.md>), [presentation](<https://devfeed.tech/tags/presentation.md>), [replication](<https://devfeed.tech/tags/replication.md>), [version](<https://devfeed.tech/tags/version.md>)

### AI overview

The San Francisco PostgreSQL User Group meeting featured a presentation of Skytools version 3, Skype's replication toolset, including Londiste and PGQ.

### Source excerpt

A presentation of Skytools version 3, the replication toolset from Skype that includes Londiste and PGQ.

## Archiving data as fast as possible

DevFeed: [Archiving data as fast as possible](<https://devfeed.tech/articles/archiving-data-as-fast-as-possible-34504.md>)

Original publisher: [Read original article](<https://tapoueh.org/blog/2013/07/archiving-data-as-fast-as-possible/>)

Author: Dimitri Fontaine PostgreSQL Major Contributor; Author

Published: 2013-07-05T13:30:00Z

Content type: tutorial

Language: en

Sources: [Dimitri Fontaine](<https://devfeed.tech/sources/dimitri-fontaine.md>)

Topics: [PostgreSQL](<https://devfeed.tech/topics/postgresql.md>), [Database](<https://devfeed.tech/topics/database.md>), [Replication](<https://devfeed.tech/topics/replication.md>), [Common Lisp](<https://devfeed.tech/topics/common-lisp.md>)

Tags: [database](<https://devfeed.tech/tags/database.md>), [lisp](<https://devfeed.tech/tags/lisp.md>), [pgq](<https://devfeed.tech/tags/pgq.md>), [postgresql](<https://devfeed.tech/tags/postgresql.md>), [replication](<https://devfeed.tech/tags/replication.md>), [standby](<https://devfeed.tech/tags/standby.md>)

### AI overview

The article describes archiving data from one PostgreSQL table to another using writable common table expressions and a single transaction. It also discusses handling foreign keys, remote archiving, and throttling the process by monitoring replication lag on a Hot Standby server.

### Source excerpt

In a recent article here we've been talking about how do do Batch Updates in a very efficient way, using the Writable CTE features available in PostgreSQL 9.1. I sometime read how Common Table Expressions changed the life of fellow DBAs and developers, and would say that Writable CTE are at least the same boost again.

## PostgreSQL Conference Europe 2012

DevFeed: [PostgreSQL Conference Europe 2012](<https://devfeed.tech/articles/postgresql-conference-europe-2012-34651.md>)

Original publisher: [Read original article](<https://tapoueh.org/conf/postgresql-conference-europe-2012/>)

Published: 2012-10-22T22:00:00Z

Content type: article

Language: en

Sources: [Dimitri Fontaine](<https://devfeed.tech/sources/dimitri-fontaine.md>)

Topics: [PostgreSQL](<https://devfeed.tech/topics/postgresql.md>), [migration](<https://devfeed.tech/topics/migration.md>), [MySQL](<https://devfeed.tech/topics/mysql.md>), [Amazon Web Services](<https://devfeed.tech/topics/aws.md>), [Website](<https://devfeed.tech/topics/website.md>)

Tags: [aws](<https://devfeed.tech/tags/aws.md>), [conference](<https://devfeed.tech/tags/conference.md>), [europe](<https://devfeed.tech/tags/europe.md>), [migration](<https://devfeed.tech/tags/migration.md>), [mysql](<https://devfeed.tech/tags/mysql.md>), [pgq](<https://devfeed.tech/tags/pgq.md>), [postgresql](<https://devfeed.tech/tags/postgresql.md>), [presentation](<https://devfeed.tech/tags/presentation.md>), [queue](<https://devfeed.tech/tags/queue.md>), [technologies](<https://devfeed.tech/tags/technologies.md>), [users](<https://devfeed.tech/tags/users.md>), [web](<https://devfeed.tech/tags/web.md>)

### AI overview

An overview of PostgreSQL Conference Europe 2012, including talks on migrating the Fotolog website from MySQL to PostgreSQL on AWS and on PGQ Cooperative Consumers for sharing load across consumers on a transactional queue. The conference took place in Prague from October 23-26, 2012.

### Source excerpt

The first talk is about a PostgreSQL Migration (from MySQL) of the Fotolog web site with 32 millions of users, 1 billion photos and 10 billion comments on those photos. The target architecture has been deployed to AWS. The second presentation is a Ligthning Talk about PGQ Cooperative Consumers, that allow sharing the load in between multiple consumers on the same transactional queue.

## PGQ Coop Consumers

DevFeed: [PGQ Coop Consumers](<https://devfeed.tech/articles/pgq-coop-consumers-34465.md>)

Original publisher: [Read original article](<https://tapoueh.org/blog/2012/03/pgq-coop-consumers/>)

Author: Dimitri Fontaine PostgreSQL Major Contributor; Author

Published: 2012-03-12T13:43:00Z

Content type: article

Language: en

Sources: [Dimitri Fontaine](<https://devfeed.tech/sources/dimitri-fontaine.md>)

Topics: [PostgreSQL](<https://devfeed.tech/topics/postgresql.md>), [Concurrent Programming](<https://devfeed.tech/topics/concurrent-programming.md>), [Job](<https://devfeed.tech/topics/job.md>)

Tags: [batch](<https://devfeed.tech/tags/batch.md>), [distributed](<https://devfeed.tech/tags/distributed.md>), [pgq](<https://devfeed.tech/tags/pgq.md>), [postgresql](<https://devfeed.tech/tags/postgresql.md>), [queue](<https://devfeed.tech/tags/queue.md>), [queues](<https://devfeed.tech/tags/queues.md>), [replication](<https://devfeed.tech/tags/replication.md>), [scale](<https://devfeed.tech/tags/scale.md>), [worker](<https://devfeed.tech/tags/worker.md>), [workers](<https://devfeed.tech/tags/workers.md>)

### AI overview

The article describes using PostgreSQL Queue (PGQ) for transactional batch processing in a high-scale architecture. It explains consolidating events from 1,280 source queues into five destination queues and using cooperative consumers to distribute processing across workers.

### Source excerpt

While working a new PostgreSQL architecture for an high scale project that used to be in the top 10 of internet popular web sites (in terms of visitors), I needed to be able to off load some processing from the main path: that's called a batch job. This needs to be transactional: don't run the job if we did rollback; the transaction, process all events that were part of the same transaction in the same transaction, etc.