Amazon Aurora vs Amazon DynamoDB: What are the differences?

Introduction

This Markdown code provides a comparison between Amazon Aurora and Amazon DynamoDB, focusing on their key differences.

1. Performance and Scalability:

   • Amazon Aurora is designed as a relational database service compatible with MySQL and PostgreSQL, providing high performance and scalability for applications that require traditional relational databases.
   • Amazon DynamoDB, on the other hand, is a fully-managed NoSQL database service, optimized for high scalability and fast performance for applications that need flexible data models.

2. Data Model:

   • Amazon Aurora is based on a relational data model, providing structured data storage with support for ACID (Atomicity, Consistency, Isolation, Durability) transactions and complex joins.
   • Amazon DynamoDB utilizes a NoSQL data model, offering a key-value store with the ability to store semi-structured data in the form of JSON-like documents. It allows flexible schema and is schema-less.

3. Architectural Approach:

   • Amazon Aurora is built as a distributed database system, using a combination of shared storage and high-performance replication across multiple Availability Zones to ensure high availability and durability.
   • Amazon DynamoDB is designed as a key-value store, offering built-in multi-AZ replication and automatic scaling capability to handle millions of requests per second without manual intervention.

4. Pricing Model:

   • In Amazon Aurora, pricing is based on a combination of database instance size and storage capacity. Customers are billed for the compute resources (e.g., CPU, memory) and storage they utilize.
   • Amazon DynamoDB employs a pay-per-usage model, where customers are billed for the provisioned throughput capacity (read and write operations per second), indexed data storage, and additional features like on-demand capacity.

5. Query Flexibility:

   • Amazon Aurora supports complex SQL queries, including joins, subqueries, and advanced analytics functions. It allows traditional relational database query processing and is suitable for applications that heavily rely on SQL.
   • Amazon DynamoDB offers limited querying capabilities, primarily focusing on simple key-value lookups and queries based on primary key attributes. It is geared towards applications that require fast data retrieval but do not rely heavily on complex querying.

6. Data Consistency:

   • Amazon Aurora provides strong consistency within each Availability Zone, ensuring that any read operation always returns the latest committed data. It supports read replicas for high availability and scalability.
   • Amazon DynamoDB offers eventual consistency by default, which means that read operations may sometimes return stale data. However, it also provides an option to choose strong consistency for specific requests, ensuring that read operations always return the most up-to-date data.

In Summary, Amazon Aurora is a performant and scalable relational database service, ideal for applications relying on structured data, complex queries, and transaction support. On the other hand, Amazon DynamoDB is a highly scalable NoSQL database service, designed for flexible data models, fast performance, and automatic scaling.