Streaming Heart Rate Data with IoT Core and QuestDB

An end-to-end demo of a simple IoT system to stream and visualize heart rate data.

Photo by Louis Reed on Unsplash

Thanks to the growing popularity of fitness trackers and smartwatches, more people are tracking their biometrics data closely and integrating IoT into their everyday lives. In my search for a DIY heart rate tracker, I found an excellent walkthrough from Brandon Freitag and Gabe Weiss, using Google Cloud services to stream data from a Raspberry Pi with a heart rate sensor to BigQuery via IoT Core and Cloud Dataflow.

Image Credit: Google Codelab

Although Cloud Dataflow supports streaming inserts to BigQuery, I wanted to take this opportunity to try out a new time-series database I came across called QuestDB. QuestDB is a fast open-source time-series database with Postgres compatibility. The live demo on the website queried the NYC taxi rides dataset with over 1.6 billion rows in milliseconds, so I was excited to give this database a try. To round out the end-to-end demo, I used Grafana to pull and visualize data from QuestDB.

Prerequisites

• NodeJS v14+
• Docker
• Google Cloud Account