Neues vom PostgreSQL Planet
Bruce Momjian: Email Etiquette
While a recent Postgres survey indicates that email lists are an impediment to new people getting involved with the project, email continues to be the primary means of communication in the community. Some of the reasons are historical, some are based on email's distributed nature, and some on email's flexibility of expression.
Pavlo Golub: Indexing `LIKE` Filters
Markus Winand wrote a great article about why and how users should use LIKE operator in their workloads. It covers different approaches like Full-Text Search, Partial Index, Trigram Index, Materialized View, and query optimization.
Luca Ferrari: Using Emacs and YASnippet to quickly write PostgreSQL functions
How a simple snippet can allow you to save time and improve your PostgreSQL code quality.
Using Emacs and YASnippet to quickly write PostgreSQL functions
I love Emacs, and I also love PostgreSQL.
Whenever I have to write PostgreSQL code, I use Emacs.
Emacs can help me improving code quality, for example to write PostgreSQL functions. I use YASnippet as a package to provide the basic template for a PostgreSQL function.
Gabriele Bartolini: How CloudNativePG manages physical replication slots for PostgreSQL in Kubernetes
Hubert 'depesz' Lubaczewski: Waiting for PostgreSQL 17 – Allow \watch queries to stop on minimum rows returned
muhammad ali: Exploring Postgres Performance: A Deep Dive into pg_stat_statements
Introduction pg_stat_statements is a built-in PostgreSQL extension that keeps track of SQL statements executed by the database server. It records details about query execution counts, total execution time and I/O related info. By capturing this information, database administrators can identify bottlenecks and optimize queries for better overall performance. In this blog, we’ll take a look […]
Samay Sharma: Tembo Stacks: Making Postgres the Everything Database
For years, Postgres has been considered among the most popular and advanced open source OLTP databases. Interestingly, 20 years ago, it was a competition between Postgres and MySQL and this debate is still going on today. 🙂 Over the last few years, Postgres added more features and its ecosystem added more extensions and now the comparison list keeps growing.
Greg Richardson: pgvector v0.5.0: Faster semantic search with HNSW indexes
Shane Borden: “Row Movement” in PostgreSQL… Is it bad?
In Oracle, right or wrong, I was always taught to try to avoid “row movement” between partitions due to the general thought that the extra workload of a “delete” + “insert” (rewrite of the row) should be avoided due to the extra I/O, index fragmentation and the associated risks of a migrating ROWID in the cases where the app developers might have used it in their code (now that’s a whole other problem). Oracle didn’t even let you do it by default.
Table by table, you had to explicitly set:
Bruce Momjian: PostgreSQL Benefits and Challenges: A Snapshot
Ivan Panchenko wrote a great article about why and how businesses should start using Postgres. It covers Postgres's structural benefits like vendor independence, code quality, and technology like NoSQL. It also covers the challenges that could be faced, like cost, time, and in-house expertise.
Francesco Tisiot: Machine Learning challenge: Chihuahua vs Muffin with PostgreSQL and pgvector
Is it a Muffin or a Chihuahua?
I tried to solve the famous meme using #PostgreSQL pgvector extension. The results are really impressive!
Do you want to try? I created a Python notebook that can give you a jump start, check it out at https://go.aiven.io/muffin-vs-chihuahua
You can find the training dataset at https://www.kaggle.com/datasets/samuelcortinhas/muffin-vs-chihuahua-image-classification
Christoph Berg: Exclusion constraints in PostgreSQL and a tricky problem
Exclusion constraints are a feature that is not very well known, but can be used to implement highly sophisticated constraints. A few years ago, Hans wrote his blog post about EXCLUDE USING GIST… WITH.
Edco Wallet: How to Postgres on Kubernetes, part 2
Peter Eisentraut: PostgreSQL make install times revisited
We continue our exploration of PostgreSQL build system performance. A long time ago, I wrote an article about how to optimize the performance of make install. This was quite helpful, as it reduced the time from 10.493 s by default to 1.654 s with some tweaks (6x faster). Now, with different hardware, a much newer PostgreSQL, and a new build system looming, let’s take another look.
Greg Richardson: pgvector v0.5.0: Faster semantic search with HNSW indexes
Regina Obe: PostgreSQL 16 64-bit for Windows FDWs
We are pleased to provide binaries for file_textarray_fdw and odbc_fdw for PostgreSQL 16 Windows 64-bit.
To use these, copy the files into your PostgreSQL 16 Windows 64-bit install folders in same named folders and then run CREATE EXTENSION as usual in the databases of your choice. More details in the packaged README.txt
These were compiled against PostgreSQL 16rc1, but should work fine against EDB PostgreSQL 16beta3.
Hubert 'depesz' Lubaczewski: Waiting for PostgreSQL 17 – Generate new LOG for “trust” connections under log_connections
Bruce Momjian: Community Edition
Related to my previous blog entry about bait and switch, I have heard people struggle to distinguish between binaries based on source code released by the Postgres community and binaries based on modifications of the community source code. The term "community edition" has often been used to represent binaries in the first category.
Hubert 'depesz' Lubaczewski: Waiting for PostgreSQL 17 – Add to_bin() and to_oct().
Christopher Winslett: HNSW Indexes with Postgres and pgvector
Postgres’ pgvector extension recently added HNSW as a new index type for vector data. This levels up the database for vector-based embeddings output by AI models. A few months ago, we had written about approximate nearest neighbor pgvector performance using the available list-based indexes. Now, with the addition of HNSW, pgvector can use the latest graph based algorithms to approximate nearest neighbor queries.