How the Tooth Fairy Manages Billions of Teeth with TimescaleDB
summary
Demonstrates using TimescaleDB to store and optimize billions of time-series IoT events: creating and configuring hypertables, using time_bucket for efficient temporal queries, automatic compression and retention policies, and continuous aggregates for fast roll-ups. Includes a live demo on real agricultural IoT data and operational lessons from seven years in production at Karnott (37 billion time-series rows, millions of daily queries).
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chapters (9)
- 0:00Introduction
- 1:48Time Scale hypertables
- 5:15Hyperfunctions demo
- 11:14Data compression
- 14:02Continuous aggregates
- 18:11Data retention
- 20:20Carnot use case
- 22:32Best practices
- 24:43Conclusion
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