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Application Data Storage in AWS with RDS and DynamoDB

Steve Suehring

AWS Relational Database Service (RDS) and DynamoDB are the primary methods for data storage in AWS. Join expert Steve Suehring as he walks you through the capabilities of both platforms. Along the way, he discusses the many types of database engines that can be used with RDS, including Amazon Aurora, MySQL, and licensed database engines such as SQL Server and Oracle, and how AWS DynamoDB, a highly scalable NoSQL implementation, integrates with other AWS services, especially when used as a data source for an Elastic Beanstalk application. By the end of the course, you'll be able to deploy an AWS database using RDS or DynamoDB and integrate that data with an AWS application service such as Elastic Beanstalk.

What you'll learn-and how you can apply it

By the end of this live, online course, you’ll understand: - AWS RDS and DynamoDB basic concepts

And you’ll be able to:

  • Deploy an RDS instance
  • Deploy a DynamoDB store
  • Create a database and data tables and insert and query data from those tables

This training course is for you because...

  • You're a database administrator who wants to better understand the features of RDS and DynamoDB.
  • You're an application architect or developer who wants to deploy applications using a cloud-based data store.
  • You're new to AWS and want to understand the capabilities of RDS and DynamoDB.


  • A basic understanding of computing, cloud, database, and NoSQL concepts

Required materials and setup:

  • An AWS account

About your instructor

  • Steve Suehring is an Assistant Professor of Computing and New Media Technologies at the University of Wisconsin-Stevens Point. Some of the courses taught by Steve include subjects like data analytics, software design, server administration, and production programming. Steve has written numerous books and has worked in industry for nearly 20 years prior to joining the faculty at UWSP.


The timeframes are only estimates and may vary according to how the class is progressing

Introduction to AWS and data storage (X minutes) - Lecture and demonstrations: Relational Database Service (RDS) basic concepts and use cases; NoSQL; DynamoDB basic concepts and use cases; obtaining code and getting started

AWS RDS capabilities (X minutes) - Lecture and demonstrations: Available database engines; snapshots and reserved instances; licensing

Deploying an RDS instance (X minutes)

  • Lecture and demonstrations: Basic, single AZ instances on Aurora; securing the instance; connecting to the instance
  • Hands-on exercise

Deploying an RDS-backed application with Elastic Beanstalk (X minutes)

  • Lecture and demonstrations: Connecting from Elastic Beanstalk; querying the database
  • Hands-on exercise

Break (10 minutes)

Configuring additional RDS options (X minutes) - Lecture and demonstrations: Controlling updates; parameter groups; option groups; reserved instances

Using clusters (X minutes)

  • Lecture and demonstrations: Cluster concepts; creating a cluster
  • Assessment checkpoint

Working with VPCs and subnet groups (X minutes)

  • Lecture and demonstrations: Subnet group concepts; creating a VPC resource; deploying the subnet group
  • Hands-on exercise

Deploying and monitoring a production-ready RDS database (X minutes) - Lecture and demonstrations: Multi-AZ deployment; applying a VPC and controlling options; viewing monitoring

AWS DynamoDB (X minutes)

  • Lecture and demonstrations: DynamoDB basic concepts; using DynamoDB on the desktop; using DynamoDB in the cloud; creating a DynamoDB Table; samples in Java
  • Hands-on exercises

Programming and monitoring with DynamoDB (X minutes)

  • Lecture and demonstrations: Integrating with PHP or Java; monitoring capabilities
  • Hands-on exercise

Integrating DynamoDB with Elastic Beanstalk (X minutes)

  • Lecture and demonstrations: Creating an Elastic Beanstalk application; integrating with DynamoDB
  • Hands-on exercise

Importing and exporting data with Data Pipeline (X minutes)

  • Lecture and demonstrations: Using Data Pipeline; exporting data; importing data
  • Hands-on exercise
  • Wrap-up and Q&A