The Postgres Guy
Postgres internals, performance, and operations — without the years of trial-and-error.
Hypercore isn't a new feature — it's a rename. The hybrid row-columnar storage engine inside TimescaleDB already existed as 'compression.' This post is the internals breakdown I wanted six months ago: chunks, compression algorithms, segmentby gotchas, and where it actually breaks.
On 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.
iqtoolkit-analyzer v0.2.6 is now live, bringing more stability and better UX for AI-powered database analysis across PostgreSQL and MongoDB. This release continues the path toward a smarter co-pilot for DB performance tuning and query optimization.
Complete your optimization journey by detecting hidden index bloat with pgtools, understanding wasted space, and implementing safe recovery strategies.
Validate fillfactor changes, troubleshoot why HOT updates still lag, and master advanced strategies to optimize your PostgreSQL update workloads.
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