Amazon DynamoDB is a NoSQL database service that delivers consistent, single-digit millisecond latency at any scale.  DynamoDB lets you easily store and query device data so you can focus on building incredible new AWS IoT solutions.

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Get started with Amazon DynamoDB on the AWS Free Tier

AWS Free Tier offers 25 GB of storage, up to 200 million requests per month with Amazon DynamoDB.

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You can be up and running with DynamoDB in minutes with our Getting Started Guide.  Below are additional resources to help you launch your IoT solution on AWS:

Building Scalable, Serverless Mobile and Internet of Things Back Ends

Ajay Nair, Senior Product Manager, AWS Lambda, Amazon Web Services
Oliver Klein, Solutions Architect, Amazon Web Services

AWS Lambda is a compute service that runs your code in response to events and automatically manages the compute resources for you. Together with Amazon Cognito, Amazon SNS push notifications, and Amazon DynamoDB, AWS Lambda is a powerful tool to build a highly scalable back end for your mobile or IoT applications. This session will take a practical approach to developing real-world IoT and mobile applications with AWS in which the back end is serverless and can scale virtually unlimited users without any infrastructure or servers to manage. This session is for those who want to get started quickly. It includes a review of key concepts and how the AWS SDKs make it easy to create powerful applications for an always-on world that connects beyond the desktop.

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Amazon DynamoDB for Big Data 

Nate Slater, Solutions Architect, Amazon Web Services

NoSQL is an important part of many big data strategies. Attend this session to learn how Amazon DynamoDB helps you create fast ingest and response data sets. We demonstrate how to use DynamoDB for batch-based query processing and ETL operations (using a SQL-like language) through integration with Amazon EMR and Hive. Then, we show you how to reduce costs and achieve scalability by connecting data to Amazon ElasticCache for handling massive read volumes. We’ll also discuss how to add indexes on DynamoDB data for free-text searching by integrating with Elasticsearch using AWS Lambda and DynamoDB streams. Finally, you’ll find out how you can take your high-velocity, high-volume data (such as IoT data) in DynamoDB and connect it to a data warehouse (Amazon Redshift) to enable BI analysis.

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Implementing a Serverless AWS IoT Backend with AWS Lambda and Amazon DynamoDB (Blog Post)
Learn how to use AWS IoT rules to trigger specific device registration logic using AWS Lamba in order to populate an Amazon DynamoDB table. Read more »

Connected Home – Command and Control (reference architecture diagram)
Integrate Alexa with your connected home devices. See the diagram »

Amazon Kinesis Streams Aggregators (GitHub repository)

Enables the automatic creation and visualization of aggregated time series data from Amazon Kinesis streams. Learn more »

Scaling Writes on Amazon DynamoDB Tables with Global Secondary Indexes (Ian Meyers, AWS Big Data Blog, Sep. 17th)
"To create our time series table, we create a table with a hash and range primary key, which allows us to look up an item using two discrete values." Read more »

From PostgreSQL to DynamoDB (Brad Van Vugt, sendwithus blog, May 1st)
"Our tables contained hundreds of millions of rows. Our indexes were growing exponentially and no longer fit in memory. Our write throughput was constantly bumping up against the maximum for a single database instance." Read more »

Amondawa provides a ReST interface for storing and querying time series data. Learn more »

Get Amondawa [Community Contributed] »