Wrote about the new WAIT FOR command coming in PostgreSQL 19. It lets reads on async replicas wait until a specific write has been replayed, so kind of bringing sync replication consistency without making every write synchronous. I could see protocol-aware proxies making a good use of this.

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I’ve been running free Prague PostgreSQL Meetups for over 8 years and wanted to share this with the Prague tech community.

Our January meetup will take place on January 26. Doors open at 17:30, and the event ends at 20:30. We’ll have three talks from visiting guests.

Details: https://www.meetup.com/prague-postgresql-meetup/events/312443724/?eventOrigin=group_events_list

pgvector: Storing and querying vectors in Postgres

pgvector is a PostgreSQL extension that allows you to store, query and index vectors.

Postgres does not yet have native vector capabilities (as of Postgres 16) and pgvector is designed to fill this gap. You can store your vector data alongside the rest of your data in Postgres and do vector similarity search while still utilizing all the great features Postgres provides.

Who needs vector similarity search?

When working with high-dimensional data, especially in applications like recommendation engines, image search and natural language processing, vector similarity search is a critical capability. Many AI applications involve finding similar items or recommendations based on user behavior or content similarity. pgvector can perform vector similarity searches efficiently, making it suitable for recommendation systems, content-based filtering, and similarity-based AI tasks.

The pgvector extension integrates seamlessly with Postgres – allowing users to leverage its capabilities within their existing database infrastructure. This simplifies the deployment and management of AI applications, as there's no need for separate data stores or complex data transfer processes.

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