Practical Time-Series Data Optimization with TimescaleDB

I explain how TimescaleDB extends PostgreSQL for time-series workloads, using HTTP request analytics to show how database design affects query speed, storage, and data retention. The course combines SQL fundamentals, query-plan inspection, and hands-on examples, then applies the concepts to an AI agent flight recorder and EV charger telemetry.

■ PostgreSQL foundations and performance
- Time-series data, SQL aggregation, EXPLAIN plans, indexes, and partitioning

■ TimescaleDB features
- Hypertables, chunk sizing, columnar storage, continuous aggregates, and approximate analytics
- Retention policies and summary hierarchies

■ Applied projects
- Local Docker setup for an AI agent flight recorder; TigerCloud for EV charger fleet telemetry

The course is aimed at PostgreSQL users building dashboards or handling growing event data. Follow along with the examples, inspect query plans and buffer usage, and use the measurements to guide choices about time filters, indexes, chunk intervals, summaries, and retention.