AWS Aurora separates compute and storage. This allows the database to scale storage independently without impacting application performance.
It automatically replicates data six times across three availability zones. This architecture improves durability and enables fast failover in the event of infrastructure failures.
An AWS Aurora cluster typically consists of:
AWS Aurora includes several cloud-native features that improve performance, availability, and scalability compared to traditional relational databases.
AWS Aurora is compatible with MySQL and PostgreSQL. This allows organizations to migrate existing applications with minimal code changes.
AWS Aurora automatically scales storage as data grows. Storage can expand up to 128 TB without manual provisioning.
It supports up to 15 read replicas with replication lag typically under 10 milliseconds. Because replicas share the same storage volume, they can improve read performance without requiring additional storage copies.
AWS Aurora Serverless v2 automatically scales compute resources based on workload demand. This helps organizations avoid overprovisioning and pay only for the capacity they use.
Amazon Aurora Global Database replicates data across multiple AWS Regions. It provides low-latency reads for global users and supports disaster recovery strategies.
Amazon Aurora automatically replicates data across multiple Availability Zones and continuously backs up data to Amazon S3. It supports point-in-time recovery and can fail over to a replica in less than a minute.
Although AWS Aurora is part of Amazon RDS, their underlying architectures are significantly different. Here’s a table showcasing the key differences between AWS Aurora and Amazon RDS.
Feature | AWS Aurora | Amazon RDS |
| Performance | Up to 5x MySQL and 3x PostgreSQL throughput | Standard engine performance |
| Read Replicas | Up to 15 | Typically up to 5 |
| Storage Scaling | Automatic up to 128 TB | Requires provisioning |
| Failover | Usually under 30 seconds | Typically 1–2 minutes |
| Storage Architecture | Shared distributed storage | Dedicated storage per instance |
So the right choice depends on your performance, scalability, and database requirements.
Choose AWS Aurora when performance, availability, and scalability are priorities.
Choose standard RDS when broader database engine support is required.
These capabilities make Amazon Aurora a popular choice for organizations running business-critical applications.
AWS Aurora delivers significantly better performance than standard MySQL and PostgreSQL deployments. It is well suited for high-traffic applications and data-intensive workloads.
Storage automatically scales from small deployments to up to 128 TB. No manual storage management is required.
AWS Aurora replicates data across multiple Availability Zones. This helps maintain uptime even during infrastructure failures.
AWS manages:
This allows teams to focus on application development instead of database maintenance.
AWS Aurora Global Database supports cross-region replication. This improves disaster recovery and user experience for globally distributed applications.
AWS Aurora offers pay-as-you-go pricing, and it depends on multiple factors.
These include:
Aurora offers two pricing options:
Additional costs may apply for Aurora Replicas, Global Database deployments, backup storage, and cross-region data transfer.
Organizations can further reduce AWS Aurora costs by leveraging AWS Database Savings Plans, which offer discounted pricing in exchange for a commitment to a consistent level of database usage over a specified term.
Follow these best practices to maximize performance and cost efficiency:
AWS Aurora is a cloud-native relational database designed for organizations that need high performance, scalability, and availability.
Its distributed architecture, Aurora Serverless capabilities, and Global Database support make it a strong choice for modern applications.
As Aurora environments grow, monitoring storage, replicas, and I/O costs becomes increasingly important. Solutions such as CloudKeeper Lens - AWS help organizations gain comprehensive visibility into database spending and identify cloud cost optimization opportunities without compromising performance.
Q1: What does AWS Aurora do?
AWS Aurora helps organizations run high-performance relational databases in the cloud. It automates tasks such as backups, scaling, replication, and failover while maintaining high availability and reliability.
Q2: Is AWS Aurora SQL or NoSQL?
AWS Aurora is a relational SQL database service that is compatible with MySQL and PostgreSQL. It supports structured data, SQL queries, transactions, and other relational database capabilities.
Q3: Is AWS Aurora Free?
AWS Aurora is a paid service. However, new AWS customers may be eligible for AWS Free Tier credits for Aurora, subject to AWS terms and conditions.
Q4: Can AWS Aurora scale automatically?
Yes. AWS Aurora automatically scales storage as data grows, while Aurora Serverless v2 can automatically adjust compute capacity based on workload demand.
Q5: When should you use AWS Aurora?
AWS Aurora is ideal for applications that require high availability, automatic scaling, and strong performance. Common use cases include SaaS platforms, e-commerce applications, and business-critical workloads.
Q6: Can I migrate an existing MySQL database to AWS Aurora?
Yes. AWS Aurora is compatible with MySQL, allowing organizations to migrate existing MySQL databases with minimal application changes. AWS also provides migration tools to simplify the migration process.
Q7: Is AWS Aurora better than Amazon RDS?
AWS Aurora generally provides higher performance, faster failover, and better scalability for MySQL and PostgreSQL workloads. Standard Amazon RDS may be more suitable when support for additional database engines is required.
