Amazon Aurora vs DynamoDB — A Comprehensive Comparison Guide

Amazon Aurora and DynamoDB are two popular database services offered by AWS, but they serve different purposes and have distinct characteristics.

Amazon Aurora is a relational database service that offers high performance and availability, with a price that's often comparable to open-source databases.

DynamoDB, on the other hand, is a NoSQL key-value and document database service that's optimized for high performance and scalability.

Amazon Aurora is designed for applications that require complex transactions and relationships between data, while DynamoDB is better suited for applications that require fast and flexible data storage.

DynamoDB features flexibility, scalability, and performance, making it a great choice for many use cases. It's no secret that I've seen many applications thrive with DynamoDB's capabilities.

DynamoDB offers high availability out of the box with no need for setup or configuration. This means you can focus on building your application without worrying about the underlying infrastructure.

DynamoDB automatically replicates your data across multiple Availability Zones within a Region to give you fault tolerance and high availability. This is a huge plus for applications that require reliability and uptime.

Here are the key features of DynamoDB at a glance:

DynamoDB automatically scales throughput capacity to meet the demands of your applications, which is a game-changer for handling large amounts of data.

Latency and performance are crucial for any database, and DynamoDB shines in this area, maintaining consistent performance as your data grows.

DynamoDB can scale both horizontally and vertically, adding more servers to the system to increase capacity and throughput, or improving the ability of a single server to handle more requests.

DynamoDB automatically scales throughput capacity to meet the demands of your applications.

DynamoDB increases the number of capacity units allocated to your table as the number of requests increases.

This enables DynamoDB to maintain consistent performance as the size of your data grows.

Latency and performance are crucial for a seamless user experience.

First, let’s compare the database access latency and query performance in detail.

Scalability is a crucial aspect of any database system, and Amazon's DynamoDB and RDS offer impressive features in this regard. DynamoDB automatically scales throughput capacity to meet the demands of your applications.

DynamoDB's horizontal scaling is a game-changer, allowing you to add more servers to increase capacity and throughput as needed. This ensures that your database can handle growing data sizes and request volumes with ease.

DynamoDB also scales vertically, improving the ability of a single server to handle more requests and data. This means you can get more out of your existing resources without having to add new servers.

Amazon RDS offers multiple database engines, including Amazon Aurora, MySQL, MariaDB, Oracle, Microsoft SQL Server, and PostgreSQL. This gives you flexibility in choosing the engine that best fits your needs.

Amazon RDS allows you to scale your database instances' storage size and performance, making it easy to adjust to changing requirements. You can also easily set up, operate, and scale a relational database in the cloud with Amazon RDS.

Here's a quick rundown of the storage sizes available for each engine:

Amazon RDS provides a cost-effective way to manage relational databases in the cloud, making it an attractive option for businesses of all sizes.

DynamoDB and Amazon Aurora offer built-in high availability and data durability through their replication mechanisms.

Data in DynamoDB is automatically replicated across multiple Availability Zones within AWS Regions, providing built-in redundancy and high availability.

This ensures that data is always accessible, even in the event of an infrastructure outage or failure.

SSDs in DynamoDB offer built-in high availability and data durability, further reducing the risk of data loss.

With single-master replication in Amazon Aurora, users can create up to 15 read-only replicas of the primary instance.

This allows for automatic failover to a read-only instance in the event of a problem with the primary instance, minimizing downtime.

Data in DynamoDB is automatically replicated to multiple Availability Zones to maintain high availability and durability, providing a low-latency read and write experience.

Data management is a crucial aspect of any database, and Amazon Aurora and DynamoDB both offer robust data management features.

Amazon Aurora supports up to 15 read replicas, which can help distribute the workload and improve performance.

DynamoDB, on the other hand, offers a feature called Global Tables, which allows for seamless data replication across regions.

When choosing a database for your application, you have two main options: Amazon Aurora and Amazon DynamoDB. Both services are developed and launched by Amazon, with Aurora launched in 2015 and DynamoDB in 2012.

Amazon Aurora is a MySQL and PostgreSQL-compatible service based on the cloud, while DynamoDB is a highly scalable database service that's compatible with Amazon's Cloud service to store databases. This means you can choose the one that best fits your needs.

One key difference between the two is how they handle referential integrity. Amazon Aurora doesn't require foreign keys, working instead on referential integrity, whereas DynamoDB doesn't work on referential integrity at all.

In terms of consistency, Amazon Aurora uses immediate consistency to ensure data is distributed equally, whereas DynamoDB uses both immediate consistency and eventual consistency.

The primary database model for Amazon Aurora is Relational DBMS, whereas DynamoDB's is a key-value store and document store. This affects how you interact with and manage your data.

Here's a comparison of the two services:

In terms of scripting, Amazon Aurora supports server-side scripting, requiring active servers, whereas DynamoDB doesn't support server-side scripting at all.

Amazon Aurora also supports a wide range of programming languages, including Ada, C, C#, C++, and many others, whereas DynamoDB supports fewer languages, including .Net, ColdFusion, and Java.

Finally, Amazon Aurora supports SQL query language, whereas DynamoDB does not.

Both DynamoDB and Aurora are fully-managed databases, freeing you up to focus on using the database rather than doing database administration.

They both fulfill high scalability requirements, with the capacity to automatically grow as needed.

DynamoDB is a NoSQL database, while Aurora is a relational database.

Aurora cluster volume can grow up to 128 Terabytes, but changing its size may take up to 15 minutes.

DynamoDB supports petabytes of data, and can seamlessly scale up or down.

Aurora provides MySQL and PostgreSQL-compatible connection interfaces to connect to the database.

Backup is a crucial aspect of data management, ensuring that your data is safe and can be restored in case of an emergency. DynamoDB has an on-demand backup and PITR, making it possible to go to any previous database state.

With DynamoDB's backup process, you don't have to worry about backup schedules and background running processes. The backup process takes little time and can be done without impacting availability or performance.

DynamoDB can back up any amount of data, and the backup recovery process is supported by a single API call. This means you can recover your data with just one click.

Aurora also offers a similar backup process without performance interruption or database service interruption. Backups are stored in an S3 bucket and can be recovered by creating a new Aurora DB cluster from the backup data.

You can create complete backups of the data in your DynamoDB tables for data archiving using on-demand backups and restore. This is especially useful for data that you want to keep for a long time.

DynamoDB's PITR offers continuous backups of the data in your DynamoDB tables, allowing you to restore the table to any second during the 35 days prior.

Amazon Aurora and DynamoDB both take security seriously, offering robust features to protect your data.

DynamoDB protects users' data at rest, in transit, and between services located in the same AWS Region.

Encryption at rest is available for both DynamoDB and Aurora using AWS KMS, which allows you to create, store, and manage encryption keys.

You have three options to encrypt DynamoDB tables with AWS KMS: an AWS-owned key at no cost, an AWS-managed key with a fee, or a customer-managed key with full control and a price.

Amazon Aurora supports both AWS-managed and customer-managed keys through AWS KMS.

Fine-grained policies in IAM users and roles limit database creation and query permissions in DynamoDB and Aurora.

Aurora DB clusters must be created in a VPC, defining its network boundary, while DynamoDB is a regional service outside the VPC boundary.

You can use VPC security groups to control which devices and Amazon EC2 instances can connect to the database instance.

Here are the encryption options for DynamoDB tables using AWS KMS: