Michael J. Freedman, the Robert E. Kahn Professor in the Computer Science Department at Princeton University, as well as the co-founder and CTO of Timescale, speaks with SE Radio host Gavin Henry about TimescaleDB. They revisit what time series data means in 2024, the history of TimescaleDB, how it integrates with PostgreSQL, and they take the listeners through a complete setup. Freedman discusses the types of data well-suited for a timeseries database, the types of sectors that have these requirements, why PostgreSQL is the best, Pg callbacks, Pg hooks, C programming, Rust, their open source contributions and projects, data volumes, column-data, indexes, backups, why it is common to have one table for your timeseries data, when not to use timescaledb, IoT data formats, Pg indexes, how Pg works without timescaledb, sharding, and how to manage your upgrades if not using Timescale Cloud. Brought to you by IEEE Computer Society and IEEE Software magazine.
Show Notes
Related Episodes
- SE Radio 484: Audrey Lawrence on Timeseries Databases
- SE Radio 583: Lukas Fittl on Postgres Performance
- SE Radio 511: Ant Wilson on Supabase (Postgres as a Service)
- SE Radio 362: Simon Riggs on Advanced Features of PostgreSQL
From IEEE
- Comparison of Time Series Databases
- TS-Benchmark: A Benchmark for Time Series Databases
- Closed Loop Benchmark for Timeseries Databases
- A Time-Position Join Method for Periodicity Mining in Time Series Databases
