PostgreSQL

Upgrade RHEL from 9.6 to 10.1 (when running PostgreSQL/Patroni)

Upgrading from RHEL 9.6 to 10.1 is not just a routine update, it’s a major platform shift. When your server runs PostgreSQL compiled from source and a Patroni-managed cluster, the complexity increases significantly. System libraries change, Python environments break,(…)

Zabbix – Monitoring full cluster Patroni/PostgreSQL

Introduction Monitoring a PostgreSQL environment involves much more than simply checking whether the database is running. In a modern high availability architecture, multiple components work together to keep the service available and stable. In this article, we will explain how(…)

Surviving a Patroni failover with logical replication

Your Patroni cluster does exactly what you built it to do. A node dies at 3 a.m., a new primary is elected in a few seconds, the application reconnects, and nobody gets paged. Your HA setup works. And(…)

pgvector, a guide for DBA – Part 2: Indexes (update march 2026)

Introduction In Part 1 of this series, we covered what pgvector is, how embeddings work, and how to store them in PostgreSQL. We ended with a working similarity search — but on a sequential scan. That works fine(…)

PostgreSQL Anonymizer: Simple Data Masking for DBAs

Sensitive data (names, emails, phone numbers, personal identifiers…) should not be freely exposed outside production. When you refresh a production database to a test or staging environment, or when analysts need access to real-looking data, anonymization becomes critical.

RAG Series – Embedding Versioning LAB

Introduction This is Part 2 of the embedding versionin, in Part 1, I covered the theory: why event-driven embedding refresh matters, the three levels of architecture (triggers, logical replication, Flink CDC), and how to detect(…)

RAG Series – Embedding Versioning with pgvector: Why Event-Driven Architecture Is a Precondition to AI data workflows

Introduction “Make it simple.” This is a principle I keep repeating, and I’ll repeat it again here. Because when it comes to keeping your RAG system’s embeddings fresh, the industry has somehow made it complicated. External orchestrators, custom Python(…)

RAG, MCP, Skills — Three Paradigms for LLMs Talking to Your Database, and Why Governance Changes Everything

Introduction Throughout my RAG series, I’ve explored how to build retrieval-augmented generation systems with PostgreSQL and pgvector — from Naive RAG through Hybrid Search, Adaptive RAG, Agentic RAG, and Embedding Versioning (not yet(…)

Oracle to PostgreSQL Migration with Flink CDC

Introduction When wanting to migrate from the big red to PostgreSQL, most of the time you can afford the downtime of the export/import process and starting from something fresh. It is simple and reliable. Ora2pg being one of the(…)

PostgreSQL 19: Two nice little improvements: log_autoanalyze_min_duration and search_path in the psql prompt

Two nice little improvements have been committed for PostgreSQL 19. The first one is about logging the duration of automatic analyze while the second one is about displaying the current search_path in psql’s prompt. Lets start with the(…)