PostgreSQL, The Time-Series Database You Want
summary
Argues PostgreSQL plus the TimeScale extension stores high‑volume time series by turning tables into hypertable chunks that auto‑partition (monthly/daily adjustable) and often speed queries versus manual inheritance; demos show identical queries returning ~17,280 rows from a single chunk and trigger‑based inheritance adding significant overhead, compression shrinks an 11.8 GB dataset to ~1 GB (≈11.96×), NYSE is cited at 6.2 billion transactions/day (~162k/s) and five years ≈5.4 trillion rows, features include continuous aggregates, columnar chunk compression, S3 cold storage and optional multi‑node access/data node scaling.
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chapters (7)
- 0:00PostgreSQL as time-series DB
- 10:18Why PostgreSQL for time-series
- 17:47Demo: Storing time-series data
- 23:49Native partitioning vs Timescale
- 31:36Timescale features: compression & aggregates
- 39:27Next steps for time-series analysis
- 43:00Q&A: Performance & scalability
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