Special Notices

In order to facilitate your AWS e-courseware and lab provision QA will need to share some of your data. For more information please view our QA Partner Data Sharing Statement. If you have any questions or concerns please contact your QA account manager.

Overview

In this course, you will learn about the process of planning and designing both relational and nonrelational databases. You will learn the design considerations for hosting databases on Amazon Elastic Compute Cloud (Amazon EC2). You will learn about our relational database services including Amazon Relational Database Service (Amazon RDS), Amazon Aurora, and Amazon Redshift. You will also learn about our nonrelational database services including Amazon DocumentDB, Amazon DynamoDB, Amazon ElastiCache, Amazon Neptune, and Amazon QLDB. By the end of this course, you will be familiar with the planning and design requirements of all 8 of these AWS databases services, their pros and cons, and how to know which AWS databases service is right for your workloads.

Prerequisites

We recommend that attendees of this course have the following prerequisites:

  • Familiarity with AWS Database Services, equivalent to AWS Database Offerings digital training
  • Understanding of database design concepts, and/or data modelling for relational or non-relational databases
  • Familiarity with cloud computing concepts
  • Familiarity with general networking and encryption concepts
  • Understanding of the three Vs of data (volume, velocity, and variety)
  • Familiarity with basic data analytics concepts, equivalent to Data Analytics Fundamentals digital training
  • Understanding of general architecting best practices and the AWS Well-Architected Framework, equivalent to Architecting on AWS classroom training

Delegates will learn how to

  • Apply database concepts, database management, and data modelling techniques
  • Evaluate hosting databases on Amazon EC2 instances
  • Evaluate relational AWS database services and their features (Amazon RDS, Amazon Aurora, and Amazon Redshift)
  • Evaluate non-relational AWS database services and their features (Amazon DocumentDB, Amazon DynamoDB, Amazon ElastiCache, Amazon Neptune, and Amazon QLDB)
  • Examine how the design criteria apply to each service
  • Apply management principles based on the unique features of each service

Outline

Module 1: Database concepts and general guidelines

  • Databases in the cloud
  • Database design principles
  • Transactional compliance

Module 2: Database planning and design

  • Workload requirements
  • Design considerations

Module 3: Databases on Amazon EC2

  • Amazon EC2 for hosting databases

Module 4: Purpose-built databases databases on Amazon EC2 and Amazon RDS

  • The journey to AWS
  • Data modelling basics

Module 5: Amazon RDS

  • Amazon RDS overview
  • Amazon RDS distinguishing features
  • Amazon RDS design considerations
  • Hands-on Lab: working with Amazon RDS databases

Module 6: Amazon Aurora

  • Amazon Aurora overview
  • Amazon Aurora distinguishing features
  • Amazon Aurora design considerations
  • Hands-on Lab: working with Amazon Aurora databases

Module 7: Amazon DocumentDB (with MongoDB compatibility)

  • Amazon DocumentDB overview
  • Amazon DocumentDB design considerations
  • Amazon DocumentDB distinguishing features
  • Hands-on Lab: working with Amazon DocumentDB databases

Module 8: Amazon DynamoDB

  • Amazon DynamoDB overview
  • Amazon DynamoDB data modelling
  • Amazon DynamoDB distinguishing features
  • Amazon DynamoDB design considerations
  • Hands-on Lab: working with Amazon DynamoDB

Module 9: Databases in Amazon Neptune

  • Amazon Neptune overview
  • Amazon Neptune design considerations

Module 10: Databases in Amazon Quantum Ledger Database (Amazon QLDB)

  • Amazon QLDB overview
  • Amazon QLDB Design Considerations

Module 11: Databases in Amazon ElastiCache

  • Amazon ElastiCache overview
  • Amazon ElastiCache for Memcached
  • Amazon ElastiCache for Redis

Module 12: Data warehousing in Amazon Redshift

  • Amazon Redshift overview
  • Amazon Redshift distinguishing features
  • Amazon Redshift data modelling
  • Amazon Redshift design considerations
  • Hands-on Lab: working with Amazon Redshift Clusters

Module 13: Course Overview

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