Expert PostgreSQL tutorials, tips, and performance optimization guides. Learn database administration, query optimization, and best practices for PostgreSQL 18 and beyond.
Posts on configuration tuning (memory, WAL, autovacuum), indexing strategies, and query optimization.
Before/after case studies showing how specific changes affected latency, throughput, or cost.
You added the index. You waited for the CREATE INDEX to finish. You re-ran the query. And EXPLAIN still shows a Seq Scan. The query is still slow. If that sounds familiar, you are not alone — it is one of the most common performance questions Houston DBAs bring up in tuning sessions. Before you […]
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 […]
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: […]
Every Houston team hits the same wall eventually: a query that used to return in milliseconds now takes 30 seconds, and production is waiting. Before you buy more RAM, spin up another replica, or shard your database, spend five minutes reading the query plan. In my years triaging slow queries, the fix is visible in […]
Connection pooling is one of the fastest ways to fix a “slow” PostgreSQL-backed app without touching a single query. In 2026, most production stacks sit behind some mix of driver-level pooling, PgBouncer, and sometimes pgpool-II—but they’re not interchangeable. This post walks through how PostgreSQL handles connections, where pooling actually helps, and when you should reach […]
Table bloat is one of PostgreSQL’s most persistent operational challenges. It’s a natural byproduct of how PostgreSQL handles updates and deletes — old row versions (dead tuples) pile up inside heap files, wasting storage, degrading index efficiency, and slowing down queries. Left unchecked, bloat can double or triple the physical size of your busiest tables. […]
PostgreSQL 18, released in late 2025, has introduced several game-changing performance features that are fundamentally altering how we design and scale database-driven applications. Among these, the arrival of native Asynchronous I/O (AIO) and first-class UUIDv7 support stand out as the most impactful for modern, high-concurrency workloads. 1. The AIO Revolution: Eliminating I/O Wait For decades, […]
The PostgreSQL 18 async I/O feature has generated a lot of excitement—and for good reason. Lab benchmarks show 2–3× better read throughput on cloud storage compared to synchronous I/O. But if you’re expecting to downsize your AWS RDS instances by 3× and pocket massive savings, I have news: real-world deployments tell a more nuanced story. […]
