iqtoolkit journal
Field notes on AI-powered database tooling, query reliability, and privacy-first DevOps workflows.
Subscribe via RSSOn AWS, comparing DocumentDB and Aurora PostgreSQL for JSON is not a simple MongoDB-vs-Postgres replay. This deep dive explains the shared decoupled storage model, where compatibility gaps show up, and what actually changes operationally.
Having managed both at scale, the answer to 'PostgreSQL or MongoDB for JSON?' is not as simple as 'MongoDB is for documents.' Deep internals on both sides will affect your performance, storage footprint, and operational burden in ways a quick benchmark won't reveal.
v0.3.0rc3 is live on PyPI with contracts-first outputs, config validation, and CLI UX improvements. Try the RC and share feedback.
Two major milestones for iqtoolkit-analyzer: v0.2.8 brings database-direct EXPLAIN analysis with contextual AI recommendations, while v0.3.0a6 delivers Google Gemini integration, MongoDB deep analysis, and multi-platform distribution (apt, dnf, zypper, Homebrew, Chocolatey).
Deep dive into PostgreSQL's TOAST (The Oversized-Attribute Storage Technique) mechanism and how it works around the fundamental 8KB block size limitation. Learn when TOAST activates, how it stores large values, and the performance implications for your database design.
PostgreSQL Internals Mastery Volume I is now available—a comprehensive foundation covering PostgreSQL architecture, memory management, storage, transactions, and durability. Learn how PostgreSQL really works at a systems level.
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