Let’s delve deep and understand the nuances of these databases.

Table of Contents

Relational Databases

Relational databases follow a table-based approach for storing data. They make use of a robust and flexible schema for setting up the data structure, where the data is stored in rows and columns. The schema is defined beforehand and requires alterations in the structure to accommodate any changes in the data. This type of database is ideal for complex queries and transactions, and it ensures ACID compliance (Atomicity, Consistency, Isolation, Durability).

In AWS, the primarily used relational database service is Amazon RDS (Relational Database Service), which supports various database engines, including MySQL, MariaDB, PostgreSQL, Oracle, and SQL Server. In addition, AWS also provides Amazon Aurora – a MySQL and PostgreSQL compatible relational database with better performance and reliability, designed expressly to leverage the capabilities of AWS.

Non-Relational Databases

Unlike relational databases, non-relational databases, often referred to as NoSQL databases, do not follow a fixed schema. They offer flexibility in managing unstructured data and can handle large amounts of data, making them suitable for big data applications. Non-relational databases are designed to provide rapid, high-volume, and wide-variety data handling.

In AWS, Amazon DynamoDB is the primary NoSQL database service. It’s a key-value and document database that delivers single-digit millisecond performance at any scale. DynamoDB is a fully managed, multi-region, multi-active, durable database with built-in security, backup and restore, and in-memory caching for internet-scale applications.

Amazon Aurora vs Amazon DynamoDB

Let’s compare Aurora and DynamoDB to understand their primary differences:

Amazon Aurora Amazon DynamoDB
Database Type Relational Non-Relational
Best For Transactional workloads, Complex joins & queries Large scale applications, Rapid, high-volume read and write workloads
Structure Table based, Fixed Schema Key-value pairs, Flexible Schema
Read/Write Speed Fast Ultra-fast, single-digit millisecond
Scaling Vertical Horizontal
ACID Compliance Yes Yes

In conclusion, the choice between Aurora and DynamoDB (i.e., between relational and non-relational databases) largely depends on your application needs. Data variety, data volume, read-write speed, complexity of queries, and scaling needs are amongst the factors that can influence this decision. As an AWS Certified Solutions Architect – Associate, being able to make an informed choice can go a long way in designing effective and efficient AWS solutions.

Practice Test

True or False: Amazon Aurora is a non-relational database service by AWS.

  • False
  • True

Answer: False

Explanation: Amazon Aurora is a relational database service provided by AWS, compatible with MySQL and PostgreSQL.

Multiple Select: Which of the following are relational databases supported by AWS?

  • Aurora
  • DynamoDB
  • PostgreSQL
  • MongoDB

Answer: Aurora, PostgreSQL

Explanation: AWS supports both Aurora and PostgreSQL as relational databases. DynamoDB and MongoDB are non-relational databases.

True or False: Relational databases are designed to handle unstructured data.

  • False
  • True

Answer: False

Explanation: Relational databases are designed for structured data. For unstructured data, non-relational databases like DynamoDB and MongoDB are used.

Single Select: Which of the following AWS services is a non-relational (NoSQL) database service?

  • Redshift
  • Aurora
  • DynamoDB
  • RDS

Answer: DynamoDB

Explanation: DynamoDB is AWS’s managed NoSQL database service.

True or False: Amazon DynamoDB supports ACID transactions.

  • False
  • True

Answer: True

Explanation: As of late 2018, Amazon DynamoDB supports ACID transactions.

Multiple Select: What are the primary benefits of using AWS Aurora as compared to a traditional relational database?

  • Dynamic scaling
  • Improved durability
  • Lower latency
  • Database encryption

Answer: Dynamic scaling, Improved durability

Explanation: AWS Aurora offers the benefits of better performance, dynamic scaling, and improved durability as compared to a traditional relational database.

True or False: A relational database arranges data into tables and links them based on data relationships.

  • False
  • True

Answer: True

Explanation: Relational databases use a structure that allows them to identify and access data in relation to other pieces of data in the database. They are based on the relational model, where data is stored in tables.

Single Select: Amazon Redshift is primarily used as a:

  • Document database
  • In-memory database
  • Key-value store
  • Data warehousing service

Answer: Data warehousing service

Explanation: Amazon Redshift is a fast, fully managed, petabyte-scale data warehousing service.

True or False: Relational databases are more flexible when it comes to changing the data structure than non-relational databases.

  • False
  • True

Answer: False

Explanation: Non-relational databases like NoSQL are more flexible when it comes to storing and manipulating unstructured data or where the data structure changes over time.

Multiple Select: Key features of Amazon DynamoDB include:

  • Managed caching
  • Automatic scaling
  • Supports SQL queries
  • In-memory processing

Answer: Managed caching, Automatic scaling

Explanation: Among its key features, DynamoDB offers managed caching and automatic scaling. However, it uses its own API (rather than SQL) for data operations and doesn’t process data in-memory like Redshift.

Interview Questions

What is the central approach of the Relational Database Service (RDS) offered by AWS?

RDS is a web-based service for backup, patches, and recovery of your relational databases. It automates these tasks to let developers focus on the upper layers of their applications instead of devoting time to the complex administration of their databases.

How does Amazon DynamoDB differ from traditional relational databases?

Amazon DynamoDB is a non-relational database service, which supports key-value and document data structures. Unlike relational databases, DynamoDB is entirely managed, significantly accelerating developers’ productivity.

What is the difference between Aurora and RDS in AWS?

While both are managed database services, Aurora is a part of RDS, designed to be completely compatible with MySQL and PostgreSQL while delivering up to five times the throughput without requiring modifications to most of the applications.

What types of databases does Amazon RDS support?

Amazon RDS supports six types of databases: Amazon Aurora, MySQL, MariaDB, Oracle, PostgreSQL, and Microsoft SQL Server.

What are the common use cases of Amazon DynamoDB?

DynamoDB is often used for mobile, web, gaming, ad tech, IoT, and many other applications that need low-latency data access.

How does AWS Aurora ensure data safety?

Aurora replicates data six ways across three AWS Availability Zones (AZs). This replication provides fault tolerance, shields database from most hardware failures, and enables high availability.

What forms of data does a non-relational database support?

Non-relational databases are flexible with the kind of data they can manage. They typically support four types of data models: Key-Value, Document, Column Family, and Graph.

What are the primary advantages of using Amazon Aurora?

Amazon Aurora provides superior performance, high availability, compatibility with MySQL and PostgreSQL, scalability, security, and a fully managed service.

Is there a limit to the storage capacity of AWS DynamoDB?

No, Amazon DynamoDB is designed to scale without limits. However, the storage size for each table is limited to 10GB.

How do relational databases manage data?

Relational databases manage data by storing it in tables with predefined schemas. The tables relate to each other using primary and foreign keys, allowing for complex querying across multiple tables.

Can you name some of the performance features of AWS Aurora?

AWS Aurora offers replication that is faster than traditional databases, automatic scaling, and read replicas for improved read traffic.

What are some use cases where non-relational databases such as DynamoDB are typically implemented?

Non-relational databases are ideal for applications that require flexibility, scalability, and speed. This includes IoT applications, time-series data, real-time data processing, content management, and any application with large and diverse data.

Can Aurora handle replication across multiple regions?

Yes, Amazon Aurora supports cross region replication. You can replicate a snapshot of your database across multiple regions for faster data access and disaster recovery.

What is Azure’s equivalent to Amazon DynamoDB?

Azure’s equivalent to Amazon DynamoDB is Azure Cosmos DB. Like DynamoDB, Cosmos DB is a fully-managed NoSQL database for modern app development.

Which AWS database service would you use for a data-warehouse type solution?

For a data-warehouse type solution, Amazon Redshift would be a suitable AWS database service.

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