amazon-timestream-tools VS dynamoquery

This is a simple demo application called the flink_connector is used to take sample load data and then stream it into the Timestream database. This project uses Amazon Kinesis to stream that data, so we need to create a stream which we can do using the following command:

Store and Access Time Series Data at Any Scale with Amazon Timestream – Now Generally Available great post from Danilo Poccia that introduces Amazon Timestream. Amazon Timestream is a time series database that makes it easy to collect, store, and process trillions of time series events per day up to 1,000 times faster and at as little as to 1/10th the cost of a relational database. Time series are a very common data format that describes how things change over time. Some of the most common sources are industrial machines and IoT devices, IT infrastructure stacks (such as hardware, software, and networking components), and applications that share their results over time. Time series information is often integrated with open source tools, and in the past I have used tools like Grafana or Kibana to dashboard this data in a way that you can begin to use to provide actionable insights. In this post, Danilo shows how you can integrate this with open source dashboard tools like Grafana, and provides a bunch of open source tools to get you going. GitHub repository here.

DynamoQuery this open source project from Altitude Networks provides and Object-Relational-Mapper (ORM) for interacting with Amazon DynamoDB, and fills a hole for Python developers who might have been looking for this. They have been using this project in house for a while now, so you know that it should be good to go. How will you use it and perhaps contribute to this project? Check out the blog, Introducing DynamoQuery: Python AWS DynamoDB ORM for more details.