Episode Details

This story was originally published on HackerNoon at: https://hackernoon.com/time-series-cardinality-why-one-more-indexed-column-costs-more-than-a-million-more-rows.
Learn how high-cardinality time-series data affects PostgreSQL index size, query planning, and ingest performance, and how schema normalization can help.
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High cardinality does not automatically mean PostgreSQL has reached its scaling limit. This benchmark shows how adding one indexed dimension can increase index size, reduce ingest throughput, and worsen planner estimates far more than adding a million rows. The article explains why wide time-series schemas amplify these costs and how moving stable descriptors into a metadata table can reduce index width, improve query performance, and keep the workload in Postgres.