Data Modeling Before Table Creation Is Essential
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In this course, we present how to create DynamoDB tables including local and secondary indices.

Learning Objectives

  • Creating DynamoDB tables using the AWS Console
  • Creating local and global secondary indices 

Intended Audience

  • Architects and developers looking to understand how to create DynamoDB Tables using the different modalities provided by AWS
  • Those studying for the AWS Solutions Architect Associate and Developer Associate certifications


  • Meet the requirements for the Cloud Practitioner certification or equivalent experience
  • Understand the fundamentals of DynamoDB as presented in the DynamoDB Basics course
  • It will help if you follow up with the Reading and Writing data in DynamoDB course

The simplest way to create a DynamoDB table is using the AWS Console. However, before creating a table in DynamoDB, it is important to consider the dataset and the access patterns that we desire to implement as we have done in the last few slides. This is going to have a direct impact on the structure and the type of queries that the table will support. A very important tool to consider when performing data modeling and creating DynamoDB tables is the AWS NoSQL Workbench. 

This is a free tool available to help you build new data models, define tables and indices, as well as import and export models. Using the NoSQL Workbench, you can set up a local downloadable version of DynamoDB and build data models as well as visualize your data and access patterns. You can also explore datasets and build operations. The sample data models that are included are also a great reference for you to get started with your own models. Be sure to download it and explore its capabilities. The download URL is shown on the screen.


About the Author
Jorge Negrón
AWS Content Architect
Learning Paths

Experienced in architecture and delivery of cloud-based solutions, the development, and delivery of technical training, defining requirements, use cases, and validating architectures for results. Excellent leadership, communication, and presentation skills with attention to details. Hands-on administration/development experience with the ability to mentor and train current & emerging technologies, (Cloud, ML, IoT, Microservices, Big Data & Analytics).