For similar capabilities to Amazon Timestream for LiveAnalytics, consider Amazon Timestream for InfluxDB. It offers simplified data ingestion and single-digit millisecond query response times for real-time analytics. Learn more [here](https://docs.aws.amazon.com//timestream/latest/developerguide/timestream-for-influxdb.html). # Getting started This section includes a tutorial to get you started with Amazon Timestream Live Analytics, as well as instructions for setting up a fully functional sample application. You can get started with the tutorial or the sample application by selecting one of the links below. **Topics** + [ # Tutorial ](getting-started.db-w-sample-data.md) + [ # Sample application ](sample-apps.md) # Tutorial Tutorial This tutorial shows you how to create a database populated with sample data sets and run sample queries. The sample data sets used in this tutorial are frequently seen in IoT and DevOps scenarios. The IoT data set contains time series data such as the speed, location, and load of a truck, to streamline fleet management and identify optimization opportunities. The DevOps data set contains EC2 instance metrics such as CPU, network, and memory utilization to improve application performance and availability. Here's a [video tutorial](https://www.youtube.com/watch?v=YBWCGDd4ChQ) for the instructions described in this section. Follow these steps to create a database populated with the sample data sets and run sample queries using the AWS Console: ## Using the console Using the console Follow these steps to create a database populated with the sample data sets and run sample queries using the AWS Console: 1. Open the [AWS Console](https://console.aws.amazon.com/timestream). 1. In the navigation pane, choose **Databases**. 1. Click on **Create database**. 1. On the create database page, enter the following: + **Choose configuration**—Select **Sample database**. + **Name**—Enter a database name of your choice. **Note** After creating a database with sample data sets, to use the sample queries which are available in the console, you can adjust the database name referenced in the query to match the database name you enter here. There are sample queries for each combination of sample data set and type of time series records. + **Choose sample data sets**—Select **IoT** and **DevOps**. + **Choose the type of time series records**—Select **Multi-measure records**. + Click on **Create database** to create a database containing two tables populated with sample data. The table names for sample data sets with multi-measure records are `DevOpsMulti` and `IoTMulti`. The table names for sample datasets with single-measure records are `DevOps` and `IoT`. 1. In the navigation pane, choose **Query editor**. 1. Select **Sample queries** from the top menu. 1. Click on one of the sample queries for a data set you chose when creating the sample database. This will take you back to the query editor with the editor populated with the sample query. 1. Adjust the database name for the sample query. 1. Click **Run** to run the query and see query results. ## Using the SDKs Using the SDKs Timestream Live Analytics provides a fully functional sample application that shows you how to create a database and table, populate the table with \$1126K rows of sample data, and run sample queries. The sample application is available in [GitHub](https://github.com/awslabs/amazon-timestream-tools/blob/master/sample_apps) for Java, Python, Node.js, Go, and .NET. 1. Clone the GitHub repository Timestream Live Analytics sample applications following the instructions from GitHub. 1. Configure the AWS SDK to connect to Amazon Timestream Live Analytics following the instructions described in [Using the AWS SDKs](getting-started-sdks.md). 1. Compile and run the sample application using the instructions below: + Instructions for the [ Java sample application](https://github.com/awslabs/amazon-timestream-tools/blob/master/sample_apps/java/README.md). + Instructions for the [Java v2 sample application](https://github.com/awslabs/amazon-timestream-tools/blob/master/sample_apps/javaV2/README.md). + Instructions for the [Go sample application](https://github.com/awslabs/amazon-timestream-tools/blob/mainline/sample_apps/goV2/README.md). + Instructions for the [Python sample application](https://github.com/awslabs/amazon-timestream-tools/blob/master/sample_apps/python/README.md). + Instructions for the [Node.js sample application](https://github.com/awslabs/amazon-timestream-tools/blob/master/sample_apps/js/README.md). + Instructions for the [.NET sample application](https://github.com/awslabs/amazon-timestream-tools/blob/master/sample_apps/dotnet/README.md). # Sample application Sample application Timestream ships with a fully functional sample application that shows how to create a database and table, populate the table with \$1126K rows of sample data, and run sample queries. Follow the steps below to get started with the sample application in any of the supported languages: ------ #### [ Java ] 1. Clone the GitHub repository [Timestream for LiveAnalytics sample applications](https://github.com/awslabs/amazon-timestream-tools/blob/master/sample_apps) following the instructions from [GitHub](https://docs.github.com/en/free-pro-team@latest/github/creating-cloning-and-archiving-repositories/cloning-a-repository). 1. Configure the AWS SDK to connect to Timestream for LiveAnalytics following the instructions described in Getting Started with [Java](getting-started.java.md). 1. Run the [Java sample application](https://github.com/awslabs/amazon-timestream-tools/blob/master/sample_apps/java) following the instructions described [here](https://github.com/awslabs/amazon-timestream-tools/blob/master/sample_apps/java/README.md) ------ #### [ Java v2 ] 1. Clone the GitHub repository [Timestream for LiveAnalytics sample applications](https://github.com/awslabs/amazon-timestream-tools/blob/master/sample_apps) following the instructions from [GitHub](https://docs.github.com/en/free-pro-team@latest/github/creating-cloning-and-archiving-repositories/cloning-a-repository). 1. Configure the AWS SDK to connect to Amazon Timestream for LiveAnalytics following the instructions described in Getting Started with [Java v2](getting-started.java-v2.md). 1. Run the [Java 2.0 sample application](https://github.com/awslabs/amazon-timestream-tools/blob/master/sample_apps/javaV2) following the instructions described [here](https://github.com/awslabs/amazon-timestream-tools/blob/master/sample_apps/javaV2/README.md) ------ #### [ Go ] 1. Clone the GitHub repository [Timestream for LiveAnalytics sample applications](https://github.com/awslabs/amazon-timestream-tools/blob/master/sample_apps) following the instructions from [GitHub](https://docs.github.com/en/free-pro-team@latest/github/creating-cloning-and-archiving-repositories/cloning-a-repository). 1. Configure the AWS SDK to connect to Amazon Timestream for LiveAnalytics following the instructions described in Getting Started with [Go](getting-started.go.md). 1. Run the [Go sample application](https://github.com/awslabs/amazon-timestream-tools/tree/mainline/sample_apps/goV2) following the instructions described [here](https://github.com/awslabs/amazon-timestream-tools/blob/mainline/sample_apps/goV2/README.md) ------ #### [ Python ] 1. Clone the GitHub repository [Timestream for LiveAnalytics sample applications](https://github.com/awslabs/amazon-timestream-tools/blob/master/sample_apps) following the instructions from [GitHub](https://docs.github.com/en/free-pro-team@latest/github/creating-cloning-and-archiving-repositories/cloning-a-repository). 1. Configure the AWS SDK to connect to Amazon Timestream for LiveAnalytics following the instructions described in [Python](getting-started.python.md). 1. Run the [Python sample application](https://github.com/awslabs/amazon-timestream-tools/blob/master/sample_apps/python) following the instructions described [here](https://github.com/awslabs/amazon-timestream-tools/blob/master/sample_apps/python/README.md) ------ #### [ Node.js ] 1. Clone the GitHub repository [Timestream for LiveAnalytics sample applications](https://github.com/awslabs/amazon-timestream-tools/blob/master/sample_apps) following the instructions from [GitHub](https://docs.github.com/en/free-pro-team@latest/github/creating-cloning-and-archiving-repositories/cloning-a-repository). 1. Configure the AWS SDK to connect to Amazon Timestream for LiveAnalytics following the instructions described in Getting Started with [Node.js](getting-started.node-js.md). 1. Run the [Node.js sample application](https://github.com/awslabs/amazon-timestream-tools/blob/master/sample_apps/js) following the instructions described [here](https://github.com/awslabs/amazon-timestream-tools/blob/master/sample_apps/js/README.md) ------ #### [ .NET ] 1. Clone the GitHub repository [Timestream for LiveAnalytics sample applications](https://github.com/awslabs/amazon-timestream-tools/blob/master/sample_apps) following the instructions from [GitHub](https://docs.github.com/en/free-pro-team@latest/github/creating-cloning-and-archiving-repositories/cloning-a-repository). 1. Configure the AWS SDK to connect to Amazon Timestream for LiveAnalytics following the instructions described in Getting Started with [.NET](getting-started.dot-net.md). 1. Run the [.NET sample application](https://github.com/awslabs/amazon-timestream-tools/blob/master/sample_apps/dotnet) following the instructions described [here](https://github.com/awslabs/amazon-timestream-tools/blob/master/sample_apps/dotnet/README.md) ------