Amazon Timestream is a fast, scalable, and serverless time series database service for IoT and operational applications that makes it easy to store and analyze trillions of events per day.
To create, query and delete the database we will use the AWS Data Wrangler an AWS Professional Service open source python initiative that extends the power of Pandas library to AWS connecting DataFrames and AWS data related services.
Paspberry Pi Configuration
Raspberry Pi OS
Python
Install Adafruit Python DHT
AWS CLI
Update Data Logger Script
The example Python script created in part 1 is updated to add the AWS Timestream logging.
Import the boto3 AWS library.
Add constants for the Timestream database and table names.
Write the temperature and relative humidity values.
The python function to write rhe records to Timestream.
Run Data Logger Script
Query AWS Timestream Database
Delete AWS Timestream Database
Summary
This post describes now to take Temperature and Relative Humidity readings from the sensor attached to the Raspberry Pi and write those readings to an Amazon Timestream database.
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This is the third in a series of posts to build a simple data logger system for temperature and relative humidity. Part 3 will use the Python Pandas package to visualize the data logged in the Amazon Timestream database.