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Build Modern Apps with Purpose-Built Databases

Offered By: Amazon Web Services via AWS Skill Builder

Tags

Amazon Web Services (AWS) Courses Database Design Courses Database Administration Courses Fraud Detection Courses Data Platform Engineering Courses

Course Description

Overview

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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