Why Your PostgreSQL Queries Get Slower Every Month

PostgreSQL queries on time series tables degrade over time because B-tree indexes must cover the entire table, forcing range queries to scan increasingly large indexes as data grows. The query planner's statistics can also fall behind on fast-growing tables, leading to suboptimal plans. TimescaleDB (sponsored) addresses this by converting tables into hypertables that automatically partition data into time-based chunks. Queries then use chunk exclusion to skip irrelevant partitions entirely — a demo shows the same 7-day range query running at 222ms on 25M rows in TimescaleDB vs. significantly slower on plain PostgreSQL. Additional TimescaleDB features covered include continuous aggregates (auto-refreshing materialized views), data retention policies that drop whole chunks cheaply, and columnar compression of older chunks achieving 90–98% storage reduction.