Table partitioning has been evolving since the feature was added to PostgreSQL in version 10. Version 11 saw some vast improvements, as I mentioned in a previous blog post. During the PostgreSQL 12 development cycle, there was a big focus on scaling partitioning to make it not only perform better, but perform better with a […]
About David Rowley
David Rowley is a PostgreSQL enthusiast and contributes regularly to 2ndQuadrant blog.
During the PostgreSQL 11 development cycle an impressive amount of work was done to improve table partitioning. Table partitioning is a feature that has existed in PostgreSQL for quite a long time, but it really wasn’t until version 10 that it started to become a highly useful feature. We’d previously claimed that table inheritance was […]
The feature freeze for the PostgreSQL 11 release is now upon us. During the last few days my colleague Álvaro Herrera pushed two changes into the development branch of PostgreSQL: 1. Faster Partition Pruning 2. Partition Pruning at Execution Time These patches aim to improve the performance and usability of the declarative table partitioning feature […]
Last year I wrote about a benchmark which I performed on the Parallel Aggregate feature that I worked on for PostgreSQL 9.6. I was pretty excited to see this code finally ship in September last year, however something stood out on the release announcement that I didn’t quite understand: Scale Up with Parallel Query Version 9.6 […]
The PostgreSQL 9.6 Release It feels like only just a few months ago that we were celebrating the release of PostgreSQL 9.5.0, but already we’re very close to the 9.6.0 release! For me personally, I’m very excited about this particular release of PostgreSQL. It was just 5 or 6 months ago that I was busy […]
A small peek into the future of what should be arriving for PostgreSQL 9.6. Today PostgreSQL took a big step ahead in the data warehouse world and we now are able to perform aggregation in parallel using multiple worker processes! This is great news for those of you who are running large aggregate queries over […]