Amazon Web Services (AWS) offers two excellent cloud SQL relational database solutions: Amazon Aurora and RDS. Both are managed database services, though they differ in the level of management involved.
Aurora is fully managed, automating most of the database maintenance tasks to simplify operations. In contrast, RDS provides a managed environment, but still allows users to maintain some control over the database cluster and member nodes.
These distinctive factors can help you determine which one is the right fit for your needs.
Here, we’ll list each database’s features, use cases, and key differences, so you can make an informed decision and select the solution that best suits your needs.
What is Amazon Aurora?
Image Source: Amazon Aurora
Amazon Aurora is a cloud-based fully managed database service compatible with the open-source databases MySQL and PostgreSQL. This means you can migrate and continue working on your existing MySQL and PostgreSQL databases without modifying the existing code.
Aurora is also an RDS database engine, so you’ll have to visit the RDS management console to opt in. Like other AWS services, it automatically backs up your data to Amazon Simple Storage Service (S3), enhancing the security of your data assets.
Features and advantages of Amazon Aurora
Aurora databases offer several features and key advantages, including:
Faster transaction processing
Aurora’s distributed storage system enables it to provide low-latency access to data, which helps with faster application processing. In addition, its compatibility with MySQL and PostgreSQL allows it to handle high-performance transactions, similar to enterprise databases.
Automatic storage resizing
Aurora offers a minimum storage space of 10 GB, which can grow up to 128 TiB in 10 GB increments. Additionally, it automatically resizes its clusters to accommodate increasing data volumes, eliminating the need for manual resource provisioning. This autoscaling aids in handling large workloads with ease.
Serverless options
Aurora serverless is an on-demand configuration of Aurora that allows you to automatically scale the compute capacity of your database with little to no downtime.
This model saves costs by charging only for the compute resources (measured in Aurora Compute Units, ACU) used at any given time. This feature allows it to handle applications with unstable usage volumes and fluctuating traffic environments.
Aurora Global Database
Aurora Global Database allows a single Aurora database to span multiple regions. This is ideal for globally distributed applications, offering sub-second database access in any region, cross-region disaster recovery, and flexible pricing.
Aurora Multi-Master
As opposed to the traditional architecture of a single-write/multi-read cluster, Aurora Multi-Master allows for multiple read-write instances across several availability zones. This architecture ensures continuous availability, even if a database instance is interrupted.
What is Amazon RDS?
Image Source: Amazon RDS
Amazon RDS is a managed relational database service. It simplifies the majority of database administration tasks, allowing you to focus on optimizing your database to meet custom needs. It also provides multiple database engines to suit your application’s performance, including:
- PostgreSQL
- RDS for Oracle
- RDS for MySQL
- RDS for MariaDB
- Microsoft SQL Server
- Amazon Aurora (compatible with MySQL and PostgreSQL)
Features and advantages of Amazon RDS
AWS RDS also provides some stand-out features and benefits, such as:
Some managed services
RDS simplifies database management by automating some routine administrative tasks like database version upgrades (which you’d need to perform manually if you were running a database on an AWS EC2 instance). This allows users to focus on higher-level operational duties like setting up parameter groups, selecting instance types, and developing applications.
Point-in-time recovery
RDS allows users to create a backup plan to improve database durability and prevent data loss. Its point-in-time recovery enables DBAs to recover data or transaction details from a specific time through backups.
Multiple database engines
RDS users can select from multiple database engines to support their application needs. For example, Oracle’s engine is best for enterprises working on complex applications, while MySQL, an open-source engine, offers more tools and libraries but limited performance levels.
Differences between Aurora and RDS
Before deciding on either Aurora or RDS as a database solution, consider how they differ in architecture, performance delivery, cost, scalability, and durability.
Database engine support
RDS offers various database engines that provide flexible application support. For example, users can simplify database migrations and prevent data loss using the AWS Data Migration Service (DMS).
On the other hand, Aurora only supports two engine types: MySQL and PostgreSQL. However, it is set up to deliver five times the performance of traditional MySQL databases and up to three times the performance of PostgreSQL databases.
Performance considerations
Compared to RDS, Aurora is specifically designed for higher performance demands. This is due to its distributed architecture, which allows it to process data faster, store more data, and guarantee low-latency access to multiple read replicas.
RDS’s performance depends on how the user customizes the database. For example, the chosen instance type, active storage configuration, and parameter groups in use all affect its overall performance. While generally more flexible, RDS may experience slower performance than Aurora, especially during maintenance operations like patching and scaling.
Scalability
Both relational databases offer vertical and horizontal scaling, but in different ways. RDS allows vertical scaling (i.e., increasing or decreasing memory and computing resources). However, this requires manual configuration to work.
Also, horizontal scaling in RDS is not automatic as it involves replication, extra read replicas (which come at a cost), and launching multiple DB instances using existing configurations.
Aurora, on the other hand, uses auto-scaling for vertical and horizontal scaling. It automatically handles a greater number of read replicas than RDS.
Scaling speed is a significant difference between the database services — RDS is slower. For example, scaling by adding extra read replicas takes time, leading to downtime. Also, you can’t reduce the storage size of an existing RDS DB instance unless you create another with less provisioned storage.
Data backups and replication
RDS provides five read replicas per database instance, and although failover is automatic for multi-AZ deployments, the result can mean longer disaster recovery times and a higher risk of data loss during downtime.
RDS also offers automatic backup through database snapshots, which store data in Amazon S3 with a retention period of up to 35 days, allowing for the creation of new instances from these snapshots.
Aurora doesn’t have this problem, since the compute and storage nodes are distinct. Each cluster can take up to 15 read replicas, guaranteeing automatic failover in milliseconds and more data storage space. This design provides continuity within the database and contributes to its high performance levels.
Availability and durability
Since the Aurora cluster has six storage nodes spread across three availability zones, the Aurora Global Database feature guarantees continuity in other AWS regions. These availability zones offer an accessibility rate of 99.99%, compared to RDS’ 99.95%. RDS also has the multi-AZ availability feature, which is dependent on the kind of DB engine in use.
Use cases
RDS suits applications with predictable workloads, such as personal projects, finance applications, and business analytics.
Aurora, especially its serverless version, is ideal for building applications that require high computing power, processing speed, and storage capacity. Examples include gaming platforms, ecommerce systems, and enterprise applications.
Cost
Aurora, known for its advanced performance and scalability features, is generally more expensive than RDS. With Aurora, you get pay-as-you-go, On-Demand, or Reserved Instance pricing. This pricing model charges users based on the instance type, storage space, and other factors.
Conversely, RDS charges you for the instance type and RDS engine in use.
Similar to how performance insights in RDS work in real time, AWS cost allocation tags help track AWS spend and resources, enabling users to minimize their cloud costs.
Aurora vs. RDS: Choosing the best AWS database solution
The most significant motivating factor when choosing a database solution should be your specific needs — that is, the kind of data queries and applications you intend to build on these databases, and the required durability and availability of the database.
Aurora may be a better option if you work in a large organization with several transactions constantly flowing. Thanks to its storage size, multiple replicas, and parallel processing capabilities, it is well-equipped to handle multiple queries simultaneously. If your concern is security or durability, you’ll also appreciate Aurora’s built-in fault tolerance and automated failover capabilities.
On the other hand, RDS is ideal for stable work environments that do not require extreme scalability and can be more cost-effective.
Keep in mind that both services offer scalability and automate administrative tasks such as patching databases with the latest security updates, backups, and failover support. Ultimately, the choice will depend on your specific requirements.
Manage your AWS Costs more efficiently with ProsperOps
Aurora and RDS are both excellent database solutions, but they have different ideal use cases and capabilities. Aurora’s high performance and adaptability make it especially suited for dynamic, intensive workloads. RDS is a more affordable, rigid solution that works better for stable workloads.
However, like all cloud-based solutions, both Aurora and RDS can add significant costs to your AWS bill. That’s where ProsperOps’ cloud cost management platform comes in.
ProsperOps automatically manages your discount commitments to optimize your Effective Savings Rate (ESR) without any manual effort on your part. Plus, you only pay ProsperOps a percentage of your savings, so you’re not adding another cloud bill to your expense sheet.
Request a ProsperOps demo today to see how we can help you save more and minimize financial risk with zero ongoing effort.