Amazon DynamoDB Data Modeling

By Mark Richman

This course teaches the skills to effectively build scalable, cost-efficient, high-performance applications using DynamoDB.

9 hours
  • 42 Lessons
  • 5 Hands-On Labs

About the course

Welcome to the Amazon DynamoDB Data Modeling course.

In this course, you will learn:

  • NoSQL concepts and DynamoDB’s features
  • How to optimize DynamoDB for:
    • Runtime performance
    • Cost
  • DynamoDB data modeling patterns
    • 1:N, N:M, hierarchical, GSI overloading, and more
    • Write sharding, sparse indexes, and materialized aggregations
    • Strategies to migrate data from RDBMS to DynamoDB

You’ll further solidify your learning with real-world examples and hands-on labs.

By the end of this course, you’ll have the necessary skills and knowledge to effectively build scalable, cost-efficient, high-performance applications using DynamoDB.

Thank you for taking the course — let’s get started!

  • Chapter 1 4 Lessons Introduction 12:01

    An Important Note About A Cloud Guru and Linux Academy Courses

    1:19

    Course Introduction

    3:11

    About the Training Architect

    0:58

    NoSQL Concepts

    6:33
  • Chapter 2 6 Lessons Understanding DynamoDB Data Structures 37:19

    DynamoDB and Tables

    11:33

    Items and Attributes

    2:51

    Partition and Sort Keys

    3:23

    Data Types

    2:59

    Indexes

    9:32

    Demo: Creating a Table

    7:01
  • Chapter 3 1 Lesson Partition Keys 6:49

    Partition Keys

    6:49
  • Chapter 4 12 Lessons Common Patterns 1:24:59

    NoSQL Data Modeling Concepts

    4:11

    One-to-Many Relationships

    8:47

    Adjacency Lists and Many-to-Many Relationships

    11:00

    Hierarchical Data

    14:52

    GSI Overloading

    8:31

    Write Sharding

    12:48

    Item Versioning

    10:54

    Sparse Indexes

    4:42

    Materialized Aggregations

    9:14

    Managing Data Relationships in DynamoDB

    0:00 Hands-On Lab

    Utilizing Write Sharding to Optimize Data Ingestion

    0:00 Hands-On Lab

    Tracking CodeCommit Metadata with DynamoDB

    0:00 Hands-On Lab
  • Chapter 5 4 Lessons Qualifying Your Workload’s Requirements 18:51

    Simple Case Study

    2:04

    Defining an Entity–Relationship Model

    5:10

    Documenting Access Patterns

    4:16

    Data Lifecycle

    7:21
  • Chapter 6 2 Lessons Interpreting Access Patterns 22:15

    Optimizing for Read/Write Workloads

    4:05

    Volume, Velocity, and Variety

    18:10
  • Chapter 7 4 Lessons Scenario 1 - User Profile Microservice 27:22

    Scenario

    4:01

    Entities and Access Patterns

    2:04

    Data Model

    21:17

    Building a Microservice Application and DynamoDB Data Model

    0:00 Hands-On Lab
  • Chapter 8 8 Lessons Scenario 2 - Relational to DynamoDB Migration 55:40

    Scenario

    2:44

    Planning Phase

    5:05

    Data Analysis Phase

    5:36

    Data Modeling Phase

    13:11

    Testing Phase

    3:01

    Data Migration Phase

    18:09

    Evolving a Data Model

    7:54

    Migrating from a Relational Database to DynamoDB

    0:00 Hands-On Lab
  • Chapter 9 1 Lesson What's Next? 1:53

    What's Next?

    1:53

What you will need

  • Amazon DynamoDB Deep Dive

What are Hands-on Labs

What's the difference between theoretical knowledge and real skills? Practical real-world experience. That's where Hands-on Labs come in! Hands-on Labs are guided, interactive experiences that help you learn and practice real-world scenarios in real cloud environments. Hands-on Labs are seamlessly integrated in courses, so you can learn by doing.

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Psst…this one if you’ve been moved to ACG!