Problems with large tables in Postgres

This post details how sharding (horizontal scaling) resolves common problems associated with large tables in PostgreSQL. It explains how partitioning and vertical scaling offer partial solutions but sharding provides a more comprehensive fix by distributing data across smaller, isolated database clusters. Specific issues addressed include: slow and late vacuuming (due to per-table operation and trigger thresholds), wasted time on incomplete repacking (where vacuum can't reclaim space due to ongoing transactions), slow queries holding connections longer (due to sequential scans, sorts, and heavy joins on large tables), and slower backups and recovery (due to large data volumes and long-running transactions). The post contrasts sharding with partitioning and vertical scaling for each problem, highlighting how isolated resources and smaller data sets on each shard mitigate these issues.