Comparing AWS Aurora and GCP Spanner

Similarities:

1. High Availability and Durability:
   • Both services are designed for high availability and durability. They automatically replicate data across multiple nodes to ensure data safety and high availability.
   • They both offer multi-region deployments for enhanced availability and global distribution.
2. Scalability:
   • Both Spanner and Aurora provide scalability, but in different ways. Spanner offers horizontal scaling and can span across multiple regions, while Aurora provides vertical scaling and read replicas for horizontal read scaling.
3. Fully Managed:
   • Both are fully managed database services, reducing the overhead of manual database administration tasks like hardware provisioning, patching, configuration, or backups.
4. Strong Consistency:
   • Google Cloud Spanner offers strong consistency in reads and writes globally, which is one of its unique features. Aurora, particularly in its Aurora Global Databases configuration, offers strong consistency within a region and eventual consistency across regions.

Differences:

1. Global Scale:
   • Spanner is designed for global scale with built-in horizontal scaling and synchronous replication across regions, which is unique compared to traditional relational databases.
   • Aurora, while highly scalable within a region and offering read replicas across regions, doesn’t inherently provide the same level of global horizontal scaling for writes.
2. Database Model:
   • Spanner combines features of both relational and NoSQL databases. It provides SQL querying capabilities with ACID transactions over a globally-distributed architecture.
   • Aurora is more of a traditional relational database, compatible with MySQL and PostgreSQL, and focuses more on improving performance and reliability of these standard RDBMS models.
3. Pricing Model:
   • The pricing models of Aurora and Spanner also differ, with Spanner charging for node hours, storage, and network usage, while Aurora charges for instance hours, I/O rate, and provisioned storage.

Conclusion:

When choosing between Amazon Aurora and Google Cloud Spanner, your decision will depend on your specific use case, global distribution needs, consistency requirements, and existing cloud infrastructure. Aurora is often chosen for applications that require a traditional relational database with high performance and scalability within AWS ecosystem, while Spanner is selected for applications needing a globally distributed, highly scalable database with strong consistency across regions.