Planning and Designing Databases on AWS (PD-DB) Online

Kursinhalt

• 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

Voraussetzungen

• Kenntnisse der AWS-Datenbankservices, die der digitalen Schulung AWS-Datenbankangebote entsprechen
• Verständnis von Datenbankdesignkonzepten und/oder Datenmodellierung für relationale oder nicht-relationale Datenbanken
• Verständnis von Cloud Computing-Konzepten
• Verständnis allgemeiner Netzwerkkonzepte und Verschlüsselungkonzepte
• Verständnis der drei Vs für Daten (Volume, Velocity und Variety)

Zielgruppe

• Dateningenieure
• Lösungsarchitekten
• Entwickler
• IT-Fachleute

Detaillierter Kursinhalt

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

Class Activity 4: Overall Picture

Challenge Lab 3: Working with Amazon Redshift clusters