Accessible Time Series Data with TimescaleDB

Explore the world of accessible time series data with TimescaleDB in this conference talk from Code BEAM America 2022. Learn how to effectively store, analyze, and display time series data using TimescaleDB, an open-source Postgres extension. Discover the unique features of TimescaleDB, including compression, continuous aggregates, and more, to build powerful applications. Gain insights into handling application metrics, financial price information, and IoT sensor data. Follow along with practical examples, such as tracking heart rate data, and understand how to leverage hypertables, time buckets, and gap-filling techniques. Ideal for developers looking to utilize time series data in their products or struggling with scaling time series aggregations.

Intro
Example: Tracking heart rate
Properties of time-series
Unique challenges of time-series
Fitness trackers
Heartbeats table
Hypertables - Chunking
Hypertables - Benefits
Fetch first and last heartbeat today
Using time bucket
Calculating beats per minute (BPM)
Filling gaps in time-series
Locf - last observation carried forward
interpolate
Hypertables - Compression
Continuous Aggregates
Example: Daily Min/MAX BPM for every user
TimescaleDB Recap
TimescaleDB - what we didn't cover
Timescale Elixir Livebook Examples