Planning and Designing Databases on AWS

Modernize your data infrastructure with advanced AWS database solutions. The Planning and Designing Databases on AWS course equips solutions architects, database architects, and developers with the skills to design both relational and NoSQL database solutions in the AWS cloud.

Course Details

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Course Overview

– • Apply database concepts, database management, and data modeling techniques
– • Evaluate hosting databases on Amazon EC2 instances
– • Evaluate relational AWS database services and their features (Amazon RDS, Amazon Aurora, and Amazon Redshift)
– • Evaluate nonrelational 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

• Familiarity with AWS Database Services, equivalent to AWS Database Offerings digital training
• Familiarity with basic data analytics concepts, equivalent to Data Analytics Fundamentals digital training
• Architecting on AWS
• Understanding of the three V’s of data (volume, velocity, and variety)
• Familiarity with cloud computing concepts & networking and encryption concepts
• Understanding of database design concepts, and/or data modeling for relational or non-relational databases

1 – Planning and Designing Databases on AWS
Course overview, structure, and database design goals
Introduction to AWS’s portfolio of database services
2 – Database Concepts and General Guidelines
Review of relational and nonrelational database fundamentals
Best practices for cloud-native database design
3 – Database Planning and Design
Workload assessment and design decision-making
Key criteria: performance, cost, scalability, and availability
4 – Databases on Amazon EC2
Self-managed databases on EC2: when and why
Trade-offs vs managed services
Cost, maintenance, and availability considerations
5 – Purpose-Built Databases on AWS
Overview of AWS’s purpose-built database strategy
Matching use cases to services (key-value, document, graph, etc.)
6 – Amazon RDS
Features and capabilities of Amazon RDS
Supported engines and deployment models
Use cases for managed relational databases
7 – Amazon Aurora
Aurora architecture and performance benefits
Aurora MySQL vs Aurora PostgreSQL
Replication, backups, and high availability
8 – Amazon DocumentDB (with MongoDB compatibility)
Designing document-based applications
Scaling and querying document data
Differences between DocumentDB and MongoDB
9 – Amazon DynamoDB
Key-value and NoSQL data models
Partitioning, throughput, and access patterns
Design best practices for performance and cost
10 – Amazon Neptune
Graph database use cases and data models
Working with Gremlin and SPARQL queries
Design considerations for connected data
11 – Amazon Quantum Ledger Database (QLDB)
Immutable ledger design and cryptographic verification
Use cases for financial records, supply chains, and auditing
How QLDB differs from blockchain and relational models
12 – Amazon ElastiCache
In-memory caching with Redis and Memcached
Boosting performance and reducing database load
Common caching patterns and considerations
13 – Amazon Redshift
Data warehousing and analytics at scale
Columnar storage and performance optimization
Redshift Spectrum and integration with AWS services
14 – Course Review and Design Application
Recap of all AWS database services
Workload matching and final design scenarios
Q&A and review exercises

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