Expert PostgreSQL tutorials, tips, and performance optimization guides. Learn database administration, query optimization, and best practices for PostgreSQL 18 and beyond.
PostgreSQL on this site is the main hub for everything related to designing, running, and improving modern Postgres databases. It brings together practical guidance on performance tuning, real‑world architecture patterns, learning resources, and hands‑on examples so developers and DBAs can get more out of PostgreSQL in production. From book recommendations and beginner tutorials to deep dives into scaling, extensions, and advanced features, this category is where readers go to level up every aspect of their Postgres stack.
OpenAI’s engineering team recently published “Scaling PostgreSQL to power 800 million ChatGPT users” — a detailed account of how ChatGPT’s primary data store survives traffic that would flatten most databases. The headline: it’s one PostgreSQL primary handling every write, roughly 50 read replicas, and a stack of operational habits that keep the write path alive. […]
Full-text search is one of those features teams assume requires Elasticsearch or a separate search service. PostgreSQL has had it built in for years: tsvector, tsquery, GIN indexes, and relevance ranking are all part of the core database. For product catalogs, document libraries, log search, and site search up to millions of rows, it is […]
OpenAI’s engineers recently shared how PostgreSQL sits at the core of ChatGPT’s infrastructure, serving 800 million users. You do not need ChatGPT-scale traffic for the lesson to apply. In Houston, the same failure pattern shows up in energy trading dashboards, medical claims pipelines, and logistics telematics fleets: the database slows down under load long before […]
PostgreSQL 19 Beta 3 shipped August 13, 2026, with minor releases 18.6, 17.11, 16.15, 15.19, and 14.24. Here is what is new, and when AWS will offer 19 on RDS and Aurora.
pgvector has become the default way to add vector search to PostgreSQL, and for good reason: you keep embeddings next to the relational data they describe, in the same database you already back up, monitor, and trust. But there is a widening gap between the demo and the production workload, and it usually shows up […]
Monitoring is the backbone of every production PostgreSQL deployment. Whether you run Patroni-managed high availability on your own hardware or Amazon Aurora in the cloud, you cannot fix what you cannot see. Yet most monitoring setups I audit collect hundreds of metrics and alert on almost none of them — or worse, they page a […]
If your Houston startup or enterprise is still running PostgreSQL on a self-managed server, Amazon RDS is one of the fastest ways to cut operational overhead. AWS handles backups, patching, failover, and storage scaling, and its managed engine keeps you on supported versions — AWS publishes guidance on when new open source engine versions land […]
Somewhere in Houston, a query that used to run in 40 milliseconds now takes 40 seconds — and the dashboard the whole team depends on is timing out. Before you buy bigger hardware, tune shared_buffers, or rewrite anything, you need to see what the planner actually decided to do. That is what EXPLAIN is for: […]
If you blinked this week, you missed a lot. In the span of a few days, the PostgreSQL ecosystem saw a major acquisition, fresh third-party benchmark results, another quarter of Microsoft’s HorizonDB preview, and — yes — someone turned PostgreSQL into a city you can walk around in. Here is the release and community news […]
Vector search is the engine room of most RAG applications in 2026, and pgvector has become the default choice for Houston teams who refuse to bolt a separate vector database onto their stack. But there is a dirty secret in the AI tooling world: most pgvector benchmarks — the ones you read and the ones […]
