Background
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.
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 and Influx line protocol compatibility. The live demo on the website queries 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.