AWS CCP Module 7: Databases

AWS Shared Responsibility Model: databases

fully managed services:

• AWS — nearly all operational tasks

• customers — design data structure, managing access controls

managed services:

• AWS — routine tasks (backup, patching, hardware provisioning)

• customers — database configuration, query optimization, performance tuning

unmanaged services:

• AWS — N/A

• customers — installation, configuration, patching, maintenance tasks, database security, backups, high availability setup, performance optimization

Q: Which statement describes the responsibilities of customers using fully managed AWS database services?

Fully managed AWS database services only require customers to be responsible for designing data structures and managing access controls.

Q: Which option describes a scenario where an unmanaged solution like a database installed directly onto an Amazon EC2 instance would be preferable to using a fully managed AWS database service?

Installing a database directly on Amazon EC2 is preferable when complete administrative control over the entire database environment is needed. This includes operating-system-level access and full configuration flexibility, which is not available in managed AWS services.

Q: AnyCompany Logistics is growing and expanding their online platform. The development team must choose between two database options. They can host their own database on an Amazon EC2 instance or use AWS's fully managed database service. The company wants to reduce IT maintenance tasks so their staff can focus more on development work.

Which option should they choose?

Fully managed AWS database services handle heavy lifting tasks like backups, patches, and high availability. This lets the development team focus on building application features that drive business value.

relational database

data relates to other pieces of data, and structured query language (SQL) is used to manage and query the data

• Amazon relational databases support popular database engines like MySQL, Postgres, Oracle

Amazon Relational Database Service (RDS)

a managed relational database service that handles routine database tasks (backups, patching, hardware provisioning)

• supports multiple database instace class types that optimize memory, performance, or I/O

how to improve data resilience with Amazon RDS

• multi-AZ deployment and automated backups

• create backups with database snapshots

Amazon RDS security features

• network isolation

• encryption in transit

• encryption at rest

what database engines does Amazon RDS support?

• Amazon Aurora

• MySQL

• Postgres

• Microsoft SQL Server

• MariaDB

• OracleDB

Amazon RDS benefits

• cost optimization — pay-as-you-go

• multi-AZ deployment

• performance optimization

• security controls

Amazon RDS use cases

• web applications

• enterprise workloads

• product inventories

Q: AnyCompany Retail wants to migrate its product database to the AWS Coud to reduce operational overhead. Their existing database contains critical inventory and pricing information that requires continuous operation with minimal downtime. Management is exploring Amazon RDS as a way to reduce the number of IT resources.

Which feature of Amazon RDS addresses the database requirements described in this scenario?

Multi-AZ deployments provide enhanced availability and durability by automatically creating database replicas in different Availability Zones. In case of infrastructure failure, Amazon RDS performs an automatic failover to the standby instance, thus ensuring that the database remains accessible with minimal disruption.

Q: Which explanation BEST describes Amazon RDS?

Amazon RDS is a fully managed database service in the AWS Cloud that frees users from most management tasks and helps set up, operate, and scale databases in the cloud.

Amazon Aurora

a managed RDS designed to help reduce unnecessary I/O operations

• compatible with MySQL and PostgreSQL

• replicates data across multiple AZs for enhanced durability and fault tolerance

Amazon Aurora benefits

• high performance and availability

  • delivers up to 5x the throughput of standard MySQL and 3x the throughput of PostgreSQL

  • distributes I/O across multiple storage nodes

• automate storage and backup management

• advanced replication and fault tolerance

Amazon Aurora use cases

• gaming applications

• media and content management

• real-time analytics

Q: AnyCompany Financial is experiencing slow response times with their current MySQL database during peak transaction periods. It processes over 100,000 transactions per hour and requires high throughput for customer satisfaction. The CTO is looking at Amazon Aurora as a way to significantly improve database performance.

Which Aurora feature BEST addresses this scenario?

The Aurora distributed storage architecture offers up to five times the throughput of standard MySQL while maintaining compatibility. It was specifically designed to handle high transaction workloads by distributing I/O across multiple storage nodes.

Q: What is a possible use case for Amazon Aurora?

Aurora provides comparable performance to high-end commercial databases but at one-tenth the cost, which makes it ideal for organizations looking to reduce database costs without sacrificing performance.

NoSQL (non-relational) database

data structure that uses key-value pairs; data is organized into items identified by unique keys

• each key has one or more associated attributes (values) that represent various characteristics of the data

• not every item in the table has to have the same attributes

Amazon DynamoDB

a fully managed NoSQL database service that provides fast and predictable performance for both documents and key-value data structures

• a powerful and fast database option for use cases that need a flexible schema

Amazon DynamoDB benefits

• scalability with provisioned capacity

• consistent high performance

  • single-digit millisecond response times at any scale

• high availability and durability

  • 99.999% data availability by replicating data across 3 distinct facilities in each AWS Region

• data encryption

Q: A staffing resource company is building an application that must store employee information with unpredictable traffic patterns. Their application requires consistent performance at all times, and the development team wants to focus on features rather than database management tasks.

Which Amazon DynamoDB capability BEST addresses the needs for this workload?

Auto scaling with provisioned capacity means that DynamoDB can automatically adjust capacity in response to actual traffic patterns. This keeps application performance consistent during unpredictable peaks in traffic, while optimizing costs during slower periods.

Q: Which statement BEST describes Amazon DynamoDB?

DynamoDB is a fully managed NoSQL database service that offers both key-value and document data models with predictable, fast performance even at scale.

Q: What is the primary way that NoSQL databases like Amazon DynamoDB differ from relational databases?

The key differentiator is that NoSQL databases offer flexible schemas that allow data to be structured in ways beyond the traditional table-based approach. This makes it possible for developers to store and process data in formats that match how their applications use it.

in-memory cache

a high-speed storage layer that temporarily stores frequently accessed data in a computer’s main memory (RAM)

• this cache will be checked first before the original data structure

  • helps reduce load on primary databases and speeds up response times

• ideal for storing session data, API responses, database query results, and other info that applications need frequently

Q: Which definition BEST describes in-memory caching?

In-memory caching is a service that stores frequently used data in memory to improve application performance and reduce the need to fetch data from slower disk-based storage.

Amazon ElastiCache

a fully managed in-memory caching service built to help reduce the complexity of adminstering in-memory caching systems

• you can use the same caching tools (e.g., Redis, Valkey, Memcached)

• automatically detects and replaces failed nodes

  • good for applications that need consistent high performance

Amazon ElastiCache benefits

• high performance for Redis, Valkey, Memcached instances

• high availability

• replication across multiple AZs

• data encryption

Amazon ElastiCache use cases

• session data management

• database query enhancement

• gaming leaderboards

Q: What is a primary benefit of using Amazon ElastiCache?

The core function of ElastiCache is to provide in-memory caching that makes it possible for applications to retrieve data from fast memory stores instead of slower disk-based databases. This significantly reduces latency and improves overall application performance.

Q: Which problem does Amazon ElastiCache solve?

ElastiCache addresses performance bottlenecks by caching frequently accessed data in memory, to reduce the load on primary databases and improve response times.

Amazon DocumentDB

a fully managed service designed to handle semistructured data (information that doesn’t conform to rigid relational schemas)

• a MongoDB compatible database

• perfect for applications needing frequent schema changes and document-oriented data

  • quickly iterate without relying on predefined schemas

Amazon DocumentDB benefits

• automatically scales storage up to 64 TB in 10 GB increments

• can handle millions of requests per second with consistent performance

• improves read throughput for high-volume applications by creating up to 15 replica instances

Amazon DocumentDB use cases

• content management system

• catalog and inventory management

• user profile and personalization system

Q: What is a primary feature of Amazon DocumentDB?

Amazon DocumentDB is specifically designed to be compatible with the MongoDB API, so existing MongoDB applications and tools will work with Amazon DocumentDB with minimal changes.

Q: What is a practical use case for Amazon DocumentDB (with MongoDB compatibility)?

Amazon DocumentDB excels at handling semistructured data like product catalogs.

AWS Backup

streamlines data protection across AWS resources and on-premise deployments by providing a single dashboard for monitoring and managing backups

• eliminates the complexity of managing multiple backup strategies by supporting multiple storage types

AWS Backup benefits

• centralized backup management

• cross-region backup redundancy

• streamlined regulatory compliance

AWS Backup use cases

• centralized disaster recovery

• consistent backup policies for compliance requirements

• consolidating multiple backup processes through 1 interface

Q: What is a feature of AWS Backup?

With AWS Backup, you can define and manage backup policies at the organization level and implement them across all related AWS accounts and Regions automatically.

Q: What is the main problem that can be solved by implementing AWS Backup?

AWS Backup addresses the challenge of managing separate backup solutions for different AWS services by providing a unified, centralized backup service across the AWS Cloud.

Amazon Neptune

a fully managed, purpose-built graph database service that manages highly connected datasets

Amazon Neptune benefits

• purpose-built for complex relationships

• high performance and scalability

• low latency queries on highly connected data

Amazon Neptune use cases

• social network user connection mapping

• fraud detection services

• search and recommendation systems

Q: What is a benefit of using Amazon Neptune?

Neptune provides low-latency and high-throughput performance for both read and write operations, making it suitable for real-time applications working with connected data.

Q: What is a practical use of Amazon Neptune?

Neptune is optimized for storing and querying highly connected data with millisecond latency.

Q: Which problem does AWS Database Migration Service (AWS DMS) solve?

A key benefit of AWS DMS is that the source database remains fully operational during migration, which minimizes downtime to applications.