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Amazon RDS vs Google Cloud SQL: What are the differences?
Amazon RDS and Google Cloud SQL are both managed relational database services that provide a platform for deploying, managing, and scaling relational databases in the cloud. While they have similar features and goals, there are several key differences between the two services.
Pricing structure: Amazon RDS offers a more flexible pricing model, allowing users to choose between different database instance types and pay for only the resources they need. On the other hand, Google Cloud SQL charges customers based on the size and location of the database instance, with limited instance types available.
Database engine options: Amazon RDS supports a wider variety of database engines, including popular options like MySQL, PostgreSQL, Oracle, and SQL Server. Google Cloud SQL, on the other hand, is primarily focused on supporting MySQL and PostgreSQL databases, with limited support for other engines.
Global scalability: Google Cloud SQL provides the ability to replicate database instances across multiple regions, allowing for global scalability and improving application performance for users located in different geographical areas. Amazon RDS also supports read replicas for scaling reads, but the replication is limited to within a single region.
Backup and recovery options: Amazon RDS offers a range of backup and restore options, including automated backups with configurable retention periods and point-in-time recovery. Google Cloud SQL provides automated backups and manual backups, but lacks the point-in-time recovery feature.
Integration with other cloud services: Amazon RDS integrates well with other AWS services, allowing users to easily connect their database instances to services like Amazon S3 for data storage or AWS Lambda for serverless computing. Google Cloud SQL also provides integration with other Google Cloud services, but the level of integration may not be as extensive as what Amazon RDS offers with AWS.
Management console and user interface: Amazon RDS provides a comprehensive management console and user interface that allows users to easily manage and monitor their database instances, set up alerts, and view performance metrics. Google Cloud SQL has a similar interface but may not offer the same level of detail and functionality as Amazon RDS.
In summary, Amazon RDS and Google Cloud SQL offer similar managed database services, but key differences include pricing structure, database engine options, global scalability, backup and recovery options, integration with other cloud services, and the management console.
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 RDS
- Reliable failovers165
- Automated backups156
- Backed by amazon130
- Db snapshots92
- Multi-availability87
- Control iops, fast restore to point of time30
- Security28
- Elastic24
- Push-button scaling20
- Automatic software patching20
- Replication4
- Reliable3
- Isolation2
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