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Amazon RDS for Aurora vs Google Cloud SQL: What are the differences?
Amazon RDS for Aurora and Google Cloud SQL are managed database services that provide scalable and highly available relational databases. Let's explore the key differences between them.
Pricing Models: Amazon RDS for Aurora follows a pay-as-you-go pricing model, where you pay for the resources you consume. On the other hand, Google Cloud SQL offers pricing options based on the number of vCPUs and the amount of memory allocated to your instances.
Replication: Aurora provides an optimized and scalable database replication mechanism, called Aurora Multi-Master, which allows for multiple active database writes across multiple Availability Zones. Google Cloud SQL, on the other hand, offers basic asynchronous replication across zones or regions for disaster recovery purposes.
High Availability: Amazon Aurora automatically replicates your data across multiple Availability Zones for high availability and data durability. In the event of a database failure, Aurora automatically fails over to a replica without any data loss. Google Cloud SQL also offers high availability through automatic failover to a replica instance, but the availability zone selection is more manual.
Scaling: Aurora supports both vertical and horizontal scaling. Vertical scaling involves increasing the instance size to handle higher workloads, while horizontal scaling involves adding read replicas to offload read traffic. Google Cloud SQL also supports vertical scaling by allowing you to change the machine type or increase the storage capacity. However, it does not provide built-in support for horizontal scaling.
Database Compatibility: Amazon Aurora is compatible with MySQL and PostgreSQL, providing the benefits of these databases along with additional performance and scalability enhancements. Google Cloud SQL supports MySQL, PostgreSQL, and SQL Server, offering native support for the respective database engines.
Monitoring and Management Tools: Amazon RDS for Aurora offers a comprehensive set of monitoring and management tools, including Amazon CloudWatch for monitoring, AWS Database Migration Service for easy migration, and AWS Management Console for database administration. Google Cloud SQL also provides monitoring and management tools, such as Cloud Monitoring and Stackdriver Logging, along with the Google Cloud Console for administration.
In summary, Aurora is known for its performance optimization and replication features, tightly integrated with the AWS ecosystem. Google Cloud SQL, on the other hand, emphasizes ease of use and seamless integration with Google Cloud services.
Using on-demand read/write capacity while we scale our userbase - means that we're well within the free-tier on AWS while we scale the business and evaluate traffic patterns.
Using single-table design, which is dead simple using Jeremy Daly's dynamodb-toolbox library
Pros of Amazon Aurora
- MySQL compatibility14
- Better performance12
- Easy read scalability10
- Speed9
- Low latency read replica7
- High IOPS cost2
- Good cost performance1
Pros of Google Cloud SQL
- Fully managed13
- Backed by Google10
- SQL10
- Flexible4
- Encryption at rest and transit3
- Automatic Software Patching3
- Replication across multiple zone by default3
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Cons of Amazon Aurora
- Vendor locking2
- Rigid schema1
Cons of Google Cloud SQL
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What is Amazon Aurora?
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