Description
Course Content
- Course Introduction
- AWS Purpose-Built Databases
- Amazon Relational Database Service (Amazon RDS)
- Amazon Aurora
- Amazon DynamoDB
- Amazon Keyspaces (for Apache Cassandra)
- Amazon DocumentDB (with MongoDB compatibility)
- Amazon Quantum Ledger Database (Amazon QLDB)
- Amazon Neptune
- Amazon Timestream
- Amazon ElastiCache
- Amazon MemoryDB for Redis
- Amazon Redshift
- Tools for Working with AWS Databases
Who should attend
This course is intended for learners in the following roles:
- Solutions architects
- Database architects
- Developers
Prerequisites
We recommend the following prerequisites for attendees of this course:
- Familiarity with AWS database services
- Understanding of database design concepts and/or data modeling for relational or nonrelational databases
- Familiarity with cloud computing concepts
- Familiarity with general networking and encryption concepts
- Completion of the digital course Introduction to Building with AWS Databases
Course Objectives
In this course, you will learn how to do the following:
- Summarize the AWS Well-Architected Framework for designing database solutions.
- Choose an appropriate purpose-built database service for a given workload.
- Design a relational database solution to solve a business problem.
- Design a NoSQL database solution to solve a business problem.
- Analyze data from multiple databases to solve a business problem.
- Discuss the security considerations for your database solution.
Outline: Planning and Designing Databases on AWS (PD-DB)
Day 1
Module 0: Course Introduction
- Course overview
Module 1: AWS Purpose-Built Databases
- Discussing well-architected databases
- Analyzing workload requirements
- Choosing the data model
- Choosing the right purpose-built database
- Knowledge check
Module 2: Amazon Relational Database Service (Amazon RDS)
- Discussing a relational database
- What is Amazon RDS?
- Why Amazon RDS?
- Amazon RDS design considerations
- Knowledge check
Module 3: Amazon Aurora
- What is Amazon Aurora?
- Why Amazon Aurora?
- Aurora design considerations
- Knowledge check
Challenge Lab 1: Working with Amazon Aurora databases
Day 2
Class Activity 1: Choose the Right Relational Database
Module 4: Amazon DynamoDB
- Discussing a key value database
- What is DynamoDB?
- Why DynamoDB?
- DynamoDB design considerations
- Knowledge check
Module 5: Amazon Keyspaces (for Apache Cassandra)
- Discussing a wide-column database
- What is Apache Cassandra?
- What is Amazon Keyspaces?
- Why Amazon Keyspaces?
- Amazon Keyspaces design considerations
- Knowledge check
Module 6: Amazon DocumentDB (with MongoDB compatibility)
- Discussing a document database
- What is Amazon DocumentDB?
- Why Amazon DocumentDB?
- Amazon DocumentDB design considerations
- Knowledge check
Module 7: Amazon Quantum Ledger Database (Amazon QLDB)
- Discussing a ledger database
- What is Amazon QLDB?
- Why Amazon QLDB?
- Amazon QLDB design considerations
- Knowledge check
Class Activity 2: Choose the Right Nonrelational Database
Challenge Lab 2: Working with Amazon DynamoDB Tables
Day 3
Module 8: Amazon Neptune
- Discussing a graph database
- What is Amazon Neptune?
- Why Amazon Neptune?
- Amazon Neptune design considerations
- Knowledge check
Module 9: Amazon Timestream
- Discussing a timeseries database
- What is Amazon Timestream?
- Why Amazon Timestream?
- Amazon Timestream design considerations
- Knowledge check
Module 10: Amazon ElastiCache
- Discussing an in-memory database
- What is ElastiCache?
- Why ElastiCache?
- ElastiCache design considerations
- Knowledge check
Module 11: Amazon MemoryDB for Redis
- What is Amazon MemoryDB (for Redis)?
- Why Amazon MemoryDB?
- Amazon MemoryDB design considerations
- Knowledge check
Class Activity 3: Let’s Cache In
Module 12: Amazon Redshift
- Discussing a data warehouse
- What is Amazon Redshift?
- Why Amazon Redshift?
- Amazon Redshift design considerations
- Knowledge check
Module 13: Tools for Working with AWS Databases
- Data access and analysis with Amazon Athena
- Data migration with SCT and DMS
