Amazon Timestream resources

Getting started with Amazon Timestream is easy: you create a database through the AWS Console, the AWS Command Line Interface (CLI), or AWS SDKs. You can send data to Amazon Timestream using data collection services such as AWS IoT Core, Amazon Managed Service for Apache Flink, and Telegraf, or through the AWS SDKs. You can use SQL to access your time series data with your preferred business intelligence tools using the JDBC driver. You can visualize and analyze time series data in Amazon Timestream using Amazon QuickSight and Grafana. You can also use Amazon SageMaker with Amazon Timestream for your machine learning needs.

For a primer on Amazon Timestream, a quick “Getting Started with Timestream” course is available to you free of cost. In this course, you will learn the benefits, typical use cases, and technical concepts of Timestream. You can easily get started with the service using the provided sample code or the interactive tool in the AWS Management Console.

Additionally, you can find more helpful content including Timestream videos, guides, and documentation below.

Videos

Introduction to Amazon Timestream (5:25)
Getting started with Amazon Timestream (26:40)
Ingesting data into Amazon Timestream with AWS IoT Core (12:57)
Ingesting data into Amazon Timestream with Apache Flink (24:16)
Visualizing Data in Amazon Timestream using Grafana (15:50)
Analyzing Data in Amazon Timestream using Amazon QuickSight (6:15)

Best Practices to Get Started

Grafana plugin

Create dashboards in Grafana to visualize your time series data using the Amazon Timestream plugin for Grafana.

Documentation »

JDBC driver

Derive insights from your time series data with your preferred business intelligence tools using the Amazon Timestream JDBC driver.

Documentation »

Apache Flink adapter

Send data from Amazon Kinesis, Amazon MSK, Apache Kafka, and other streaming technologies directly into Amazon Timestream using the Apache Flink adapter.

Documentation »

Telegraf connector

You can send time series data collected using open source Telegraf directly into Amazon Timestream using the Telegraf connector.

Documentation »

Amazon SageMaker Notebook

You can use Amazon SageMaker notebooks to integrate your machine learning models with Amazon Timestream.

Documentation »

Documentation

Amazon Timestream Developer Guide »
Provides a conceptual overview of Amazon Timestream and instructions for using the various features with both the AWS Management Console and the AWS command line interface (CLI).

AWS CLI Reference for Amazon Timestream »
Describes how to use the AWS command line interface (CLI) to control Amazon Timestream.

SDKs

You can access Amazon Timestream using the Java, Go, Python, and Node.js SDKs. Get started with the Amazon Timestream SDKs in the documentation.