Maintaining Large Tables in PostgreSQL

This talk focuses on the real problems large tables create at scale: autovacuum falling behind, bloat accumulating silently, planner misestimation, WAL explosions, and maintenance operations colliding with production traffic. Rather than treating these as isolated issues, we’ll examine them as symptoms of unsustainable data growth.

Using PostgreSQL (with specific considerations for Azure Database for PostgreSQL), the session walks through practical strategies to sustain performance over time: per-table autovacuum tuning, bloat and statistics management, maintenance options, and observability guardrails.

Finally, we’ll address the critical architectural questions: when is a large table no longer the right abstraction? We’ll compare options such as partitioning, hot/cold splits, rollup tables, sharding, and offloading analytical workloads.