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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
Overview
