Introduction to Data Stores in AWS

1. Introduction to Data Stores in AWS

Welcome to Chapter 1 of this course on AWS Data Stores. I'm Dunieski Otano, an AWS Solutions Architect with 16 AWS certifications and nearly a decade of cloud experience. I've helped organizations design scalable and secure data solutions, and I'm excited to share practical insights to help you understand AWS data stores. So, let's dive in.

2. Choosing the right AWS data store

One of the hardest parts of working with AWS is knowing which data store to choose. With dozens of storage services available, how do you decide what's right for your application? Should you use a database or object storage? What about caching? In this course, we'll cut through the complexity and focus on the four foundational data stores that handle the majority of real-world use cases. By the end, you'll know exactly when to use each service and why.

3. AWS storage overview

Choosing the right storage service is critical for application performance, cost, and scalability. AWS offers a comprehensive set of data storage services: file storage with EFS and FSx, block storage with EBS, object storage with S3, databases like DynamoDB and RDS, caching with ElastiCache, search with OpenSearch, and backup solutions with AWS Backup.

4. Understanding block, file, and object storage

While we're not focusing on block and file storage, let's briefly understand each type. Block storage provides raw storage volumes that attach to EC2 instances like traditional hard drives: think EBS for your server's disk. File storage offers shared file systems where multiple servers can access the same files simultaneously: like EFS for shared application data. Object storage stores files as objects accessed via API with unlimited scalability: that's S3, which we'll cover in depth. Understanding these differences helps you choose the right storage type for your workload.

5. Relational vs non-relational databases

Let's clarify a key concept: relational versus non-relational databases. Relational databases like Amazon RDS use structured tables with fixed schemas - perfect for complex queries with joins and transactions. Non-relational databases, or NoSQL like DynamoDB, use flexible data models without fixed schemas. DynamoDB excels at high-performance, scalable applications by trading complex joins for speed and flexibility. Understanding this distinction helps you choose between DynamoDB and relational databases for your application needs.

6. This course focuses on

In this course, we're focusing on four services that form the foundation of most AWS applications: S3, DynamoDB, ElastiCache, and OpenSearch. Let's look at when to use each one.

7. Building an e-commerce application

Let's see how these services work together in a real application. Imagine you're building an online store. You would use S3 to store all your product images and videos. DynamoDB would hold user profiles and shopping cart contents for fast access. ElastiCache would cache your most popular product details so they load instantly. And OpenSearch would power the search bar, letting customers find products quickly. Throughout this course, we'll dive deep into each of these services.

8. What you'll learn in this course

The key to mastering AWS data stores isn't memorizing features: it's understanding when to use each service. In the next video, we'll explore data access patterns and consistency models. You'll learn how to identify whether your application is read-heavy or write-heavy, when to prioritize speed over consistency, and how to make informed decisions that balance performance, cost, and reliability. Let's get started.

9. Let's practice!

Let's now practice what we have learned!

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