The 3 PostgreSQL Blogs Every Data Engineer Should Read in 2026
PostgreSQL continues to dominate as the most admired and widely adopted relational database, and the ecosystem around it is richer than ever. If you work with Postgres in production, choosing a few high‑signal blogs to follow can keep you ahead of performance issues, new features, and architectural best practices.
1. Planet PostgreSQL: The Community Firehose
If you only follow one PostgreSQL resource, make it Planet PostgreSQL. It is the official community blog aggregator that pulls in posts from core contributors, major vendors, and independent experts around the world.
Planet PostgreSQL is where you see new ideas first: query planner deep dives, release walk‑throughs, battle stories from very large deployments, and announcements from prominent tools and extensions. For anyone building or operating serious Postgres systems, subscribing to its feed is essentially table stakes.
Link: https://planet.postgresql.org
2. EDB Postgres Blog: Enterprise-Grade Postgres in the Real World
The EDB Postgres blog focuses on how to run PostgreSQL at scale in demanding enterprise environments. Posts there frequently cover performance tuning, high availability, migration strategies, and what new features in recent releases mean for production workloads.
Because EDB employs multiple long‑time community contributors and committers, their articles often bridge the gap between upstream internals and day‑to‑day operational concerns like upgrades, replication, and compliance. If you are responsible for mission‑critical databases, EDB’s content is especially valuable.
Link: https://www.enterprisedb.com/blog
3. Timescale Blog: Time-Series, Observability, and Modern Workloads
The Timescale blog brings a specialized angle: time‑series, observability, and analytics on top of PostgreSQL. They publish tutorials and design patterns for handling metrics, events, and IoT data using SQL and PostgreSQL’s extension ecosystem.
Beyond time‑series itself, Timescale’s team regularly writes about performance, schema design for large append‑only workloads, and how to keep query latency under control as data volumes grow. If your Postgres cluster doubles as both OLTP store and analytics engine, this blog is an excellent source of pragmatic guidance.
