Database
PostgreSQL at scale
Operating PostgreSQL when the dataset and write rate stop fitting on a single instance — partitioning, replication, vacuum tuning, and the managed-service landscape.
PostgreSQL is now the default database for most new applications; the operational complexity of running it at scale used to be a major drawback, but the managed-service ecosystem (Aurora, AlloyDB, Neon, Supabase, RDS) and the extension ecosystem (Citus, TimescaleDB, pgvector) have closed most of that gap.
Notifire's coverage tracks the releases and tooling that change the cost-or-complexity curve: logical replication maturity, partition routing, vacuum behaviour under high write load, and the connection-pooling layer (PgBouncer, pgcat) that sits in front of nearly every production deployment.
Latest briefings on PostgreSQL at scale
Data
New Postgres extension improves data handling
A new version of pg_sorted_heap, a PostgreSQL extension, has been released. It introduces physically sorted storage and integrated vector search. Version 0.14.0 adds official support for PostgreSQL 16 and is now available on the PostgreSQL Extension Network (PGXN) for easier installation and management.
Taranpreet Singh ·
Data
ChatFeatured boosts AI analytics performance
AI brand discovery platform ChatFeatured migrated its analytics database from PlanetScale Postgres to a Postgres-compatible service managed by ClickHouse. The switch, completed in 30 minutes, reduced complex query times from 2.5 minutes to under one second, significantly improving performance for its AI-powered features.