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Amazon Web Services

Build Modern Apps with Purpose-Built Databases

Amazon Web Services and Amazon via AWS Skill Builder

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Overview

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In this six-course curriculum, you will learn the value and process of using purpose-built databases in the AWS Cloud. This curriculum includes tutorials of five purpose-built databases on Amazon Web Services (AWS). You will use a restaurant review and rating application as a guiding example.

• Skill level: Intermediate

• Duration: 3 hours


Activities

This curriculum includes courses with presentations and video demonstrations.


Curriculum objectives

In this curriculum, you will learn to:

• Explain the value of using purpose-built databases to meet specific application needs.

• Identify the factors you need to consider when choosing purpose-built databases.

• Design an Amazon DynamoDB database for a restaurant review and rating application.

• Add caching to your restaurant review and rating application using Amazon ElastiCache.

• Add a fraud-detection service with Amazon Neptune for storage.

• Manage marketing resources with Amazon DocumentDB (with MongoDB compatibility) for storage.

• Add a user management service to your application with Amazon Keyspaces (for Apache Cassandra) for storage.


Audience

This curriculum is intended for:

• Customers, Amazonians, and AWS Partners who have experience with AWS, including a background in database administration and design

• Data platform engineers

• Database developers

• Solutions architects


Prerequisites

We recommend that attendees of this curriculum have:

• A basic understanding of databases, including maintenance and support

• Completed the AWS Planning and Designing Databases course 


Curriculum outline

Course 1: Getting Started with Purpose-Built Databases

• Lesson 1. Introduction

• Lesson 2. Why Purpose-Built Databases?

• Lesson 3. Factors to Consider

• Lesson 4. Next Steps


Course 2: High Performance and Scale with Amazon DynamoDB

• Lesson 1. Introduction

• Lesson 2. Step 1: Create an AWS Cloud9 Environment

• Lesson 3. Step 2: Prepare for Data Modeling with DynamoDB

• Lesson 4. Step 3: Plan Your Data Model and Create a DynamoDB Table

• Lesson 5. Step 4: Interact with DynamoDB in Your Application

• Lesson 6. Step 5: Clean Up Resources

• Lesson 7. Conclusion


Course 3: Caching for High-Volume Workloads with Amazon ElastiCache

• Lesson 1. Introduction

• Lesson 2. Step 1: Create an AWS Cloud9 Environment

• Lesson 3. Step 2: Create a Redis Instance by Using ElastiCache

• Lesson 4. Step 3: Implement a Cache-Aside Strategy with Your Instance

• Lesson 5. Step 4: Clean Up Resources

• Lesson 6. Conclusion 


Course 4: Graph Relationships with Amazon Neptune

• Lesson 1. Introduction

• Lesson 2. Step 1: Create an AWS Cloud9 Environment

• Lesson 3. Step 2: Create a Neptune Database

• Lesson 4. Step 3: Design Your Graph Data Model and Load Sample Data

• Lesson 5. Step 4: Use a Graph Database in Your Application

• Lesson 6. Step 5: Clean Up Resources

• Lesson 7. Conclusion


Course 5: Document Storage with Amazon DocumentDB

• Lesson 1. Introduction

• Lesson 2. Step 1: Create an AWS Cloud9 Environment

• Lesson 3. Step 2: Create an Amazon DocumentDB Database

• Lesson 4. Step 3: Design a Document Data Model and Load Sample Data

• Lesson 5. Step 4: Use Amazon DocumentDB in Your Application

• Lesson 6. Step 5: Clean Up Resources

• Lesson 7. Conclusion


Course 6: Scalability and Familiarity with Amazon Keyspaces

• Lesson 1. Introduction

• Lesson 2. Step 1: Create an AWS Cloud9 Environment

• Lesson 3. Step 2: Create an Amazon Keyspaces Table

• Lesson 4. Step 3: Insert, Read, and Delete Data with Amazon Keyspaces

• Lesson 5. Step 4: Clean Up Resources

• Lesson 6. Conclusion

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