AWS Aurora

Among other services, Amazon also provides Aurora - a database service with a global presence that is compatible with MySQL and PostgreSQL at a mere tenth of the cost of traditional databases. True to AWS fashion, Amazon fully manages these databases helping to further reduce costs for the users and alleviate the need to dedicate resources towards maintenance. To prevent loss and damage, Aurora databases have nearly a 100% uptime with easy replication and a restoration of services in less than a minute. For newer users to AWS, immigrating data locally is incredibly easy.

What is Aurora’s Role?

Amazon Aurora is a highly efficient and cost-effective database service with a global presence. It is compatible with MySQL and PostgreSQL, making it an ideal choice for users already familiar with these database systems. One of the significant advantages of Amazon Aurora is its affordability, as it costs only a fraction of traditional databases while offering comparable performance.

What sets Amazon Aurora apart is its fully managed approach by Amazon Web Services (AWS). With AWS handling all the database management tasks, including maintenance and updates, users can focus on their core business activities without worrying about the backend infrastructure. This not only reduces costs but also ensures that the databases are always up to date with the latest features and security patches. It boasts nearly 100% uptime, thanks to its reliable replication capabilities and quick restoration of services in less than a minute. This high availability ensures that applications relying on Aurora databases can operate uninterrupted, even in the event of hardware failures or other disruptions. For users new to AWS, migrating data to Amazon Aurora is a seamless process. With easy data import and export functionality, users can effortlessly transition their databases from local environments to Aurora, minimizing downtime and ensuring a smooth transition.

However, it’s worth noting that the pricing structure for Aurora can become complex. Factors such as data stored per month, storage and I/Os utilized, backup storage requirements, and data transfers contribute to the final cost. Amazon provides a comprehensive pricing guide to assist new users in accurately estimating costs before committing to any specific plan. While Aurora offers impressive performance and scalability, it is still limited by the capabilities of MySQL and PostgreSQL. Users should be aware of the specific features and functionalities available within these database systems to ensure they meet their requirements.

Main Features


Performance and Scalability

Aurora’s architecture significantly contributes to its high performance and scalability through its design and operational features. Firstly, Aurora is engineered with an optimized architecture that enhances both speed and consistency even under demanding workloads. This is achieved by utilizing distributed storage systems along with mechanisms for parallel processing of queries, which together improve the overall throughput.

In terms of scalability, Aurora offers different functionalities based on the configuration. Standard Aurora instances, while not supporting vertical scaling (in terms of CPU, storage, or memory expansion on demand), do feature an autoscaling capability for storage, ensuring that database capacity can dynamically adjust as needed. Moreover, the Aurora Serverless option elevates scalability to a new level by automatically adjusting computing resources based on the actual usage, thereby efficiently managing changes in load without manual intervention. This ability to scale resources automatically ensures both flexibility and cost-efficiency in resource management.


    • Higher throughput - Utilizing a variety of software and hardware techniques, Aurora can maximize the capabilities of MySQL and PostgreSQL, resulting in a significant increase in throughput by up to 3x and 5x, respectively. The enhanced efficiency does not compromise consistency. Additionally, scaling up throughput is made possible by creating up to 15 database replicas equipped with the same functionalities as the base instance.
    • Parallel Query - The implementation of parallel query processing allows for simultaneous execution of multiple queries, resulting in faster query speeds and optimized processing power, effectively reducing traffic congestion.
    • Serverless - Similar to other AWS services, Aurora effortlessly adjusts the required resources based on current or anticipated traffic demands through RDS APIs or the AWS Management Console. Storage capacity can be easily adjusted, ranging from as low as 10 GB to as high as a massive 128 TB of data storage.
    • Customizable Endpoints - Introducing new instances allows for the strategic distribution of workloads, with customizable endpoints enhancing flexibility in managing data access points.
    • Amazon DevOps Guru - By leveraging integrated monitoring tools such as Amazon DevOps Guru, Aurora can effectively track and analyze traffic patterns to identify potential bottlenecks and performance issues. This proactive approach enables the system to detect and address root causes of poor performance, ensuring optimal operation and user experience.

Availability and Durability

    • Repairs and Monitoring - With Amazon RDS, you can rest assured knowing that your Aurora instance is constantly monitored. In the event of a database failure, the instance will be automatically restarted, minimizing downtime. To further enhance availability, crash recovery replay is not required, enabling faster restart times.
    • Global Presence - AWS understands the importance of minimizing latency and ensuring data availability. That’s why they have localized infrastructure within multiple geographical regions. By leveraging secondary regions as backups, you can safeguard against any potential outages, ensuring uninterrupted access to your databases.
    • Faults and Self-Repair - Amazon RDS and Aurora employ robust fault-tolerant mechanisms. Every 10 GB of data in your database is replicated across six different copies, distributed across three availability zones. This redundancy ensures that even in the event of hardware failures or other issues, your read-write capabilities remain unaffected, guaranteeing continuous access to your data.
    • Snapshots and Backups - Taking snapshots of your database is a breeze with Amazon RDS. These user-initiated backups are stored securely in Amazon S3 and can be retained until you explicitly delete them. In the case of Aurora, the Backtrack feature allows you to revert to a previous point in time without relying on a backup, preventing any user errors. This level of flexibility empowers you to efficiently manage your data and restore it when needed.


    • Network Isolation - Using Amazon’s in-house Virtual Private Cloud (VPC), Aurora instances get a private connection to on-premises infrastructure with industry-standard VPN encryption.  Firewalls can be individually configured per DB instance.
    • Permission - Amazon’s Identity and Access Management (IAM), users can establish who has access to what to prevent breaches in the circumstances of a compromised user.
    • Threat Detection - Amazon’s GuardDuty monitors logins and checks for suspicious activity, catching potential threats on their way to stored data.

Constant Upkeep

    • Ease of Use - Initiating a new instance isn’t hard.  Generating a new Aurora DB instance is just a matter of a single API call or a button press on the RDS Management Console.  With just as many clicks, it is easy to shut down or restart the instance.
    • Monitoring - AWS CloudWatch provides metrics for the DB at no extra cost from memory to storage, throughput, and connectivity.
    • Software Updates - Updates are applied automatically to the user’s configuration.  This includes whether or not to update and when to update.  Existing sessions are also preserved during the updating process, resulting in at most a few seconds of dropped throughput.

Supported Migrations

    • MySQL DB
    • PostgreSQL DB
    • Commercial DB
    • Babelfish - For migrating off of legacy SQL databases.


Amazon Aurora operates on a pay-as-you-go model, with the option to choose Reserved Instances or On-Demand pricing. The pricing structure for Aurora is based on a cluster configuration, encompassing charges for DB instances, I/O, and storage. It’s worth noting that any optional features activated will be factored into the billing as well. Factors such as the amount of data stored per month, storage and I/Os utilized, backup storage requirements, Backtrack usage, snapshot or cluster exports, and data transfers all contribute to the final cost. While these pricing factors can become complex quickly, Amazon provides a comprehensive pricing guide to assist new users in accurately estimating costs before committing to any specific plan. These costs get extremely complicated very quickly, and Amazon provides a pricing guide here for new users to calculate pricing quickly before they sign up.

In comparison, traditional RDBMS solutions typically involve significant licensing and ongoing maintenance costs, which can make them more expensive over time. Aurora’s efficient performance and lower infrastructure needs not only reduce these costs but also provide a scalability advantage that is not as easily achievable with conventional databases. Moreover, RDS offers a similar pay-as-you-go pricing model, which allows users to closely align their expenses with their actual usage. This model is particularly beneficial for businesses looking for cost flexibility without the commitment to extensive upfront payments. However, while RDS provides this flexibility, Aurora brings an optimal blend of high performance and cost-effectiveness, making it an attractive alternative for those looking to optimize their database management costs.


Dolan Cleary

Dolan Cleary

I am a recent graduate from the University of Wisconsin - Stout and am now working with AllCode as a web technician. Currently working within the marketing department.

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