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Google Cloud SQL vs Heroku Postgres: What are the differences?
Introduction: In this article, we will compare Google Cloud SQL and Heroku Postgres - two popular database services. We will outline the key differences between them, focusing on specific aspects.
Pricing Models: Google Cloud SQL offers various pricing models, including pay-as-you-go and commitment-based plans, allowing users to choose the most suitable option. On the other hand, Heroku Postgres primarily offers a pay-as-you-go pricing model, with different tiers based on the desired features and performance.
Infrastructure Management: Google Cloud SQL handles the management of the underlying infrastructure, including scaling, backups, and replication, relieving the users from this responsibility. In contrast, Heroku Postgres requires users to manage the infrastructure themselves, offering more control but also more administrative overhead.
Integration with Ecosystem: Google Cloud SQL seamlessly integrates with other Google Cloud Platform services, such as Compute Engine and App Engine, enabling easy data access and utilization. Heroku Postgres, being a part of the Heroku platform, integrates well with Heroku's ecosystem, which includes seamless deployment, scaling, and monitoring of applications.
Scaling Options: With Google Cloud SQL, users can easily scale their databases vertically by adjusting the machine type, as well as horizontally by utilizing read replicas. Heroku Postgres also supports vertical scaling but has limited options for horizontal scaling, making it more suitable for smaller or medium-sized applications.
Data Insights and Analysis: Google Cloud SQL provides integration with Google's BigQuery, a powerful analytics data warehouse, allowing for advanced data analysis and insights. Heroku Postgres, while offering basic data analysis capabilities, may require additional configurations and tools to perform complex analytics tasks.
High Availability and Disaster Recovery: Google Cloud SQL offers built-in high availability through automatic failover and replication to multiple zones, ensuring data durability and continuous operation. Heroku Postgres also provides high availability options but may require additional setup and configuration to achieve the same level of robustness.
In Summary, Google Cloud SQL and Heroku Postgres differ in terms of pricing models, infrastructure management, ecosystem integration, scaling options, data analysis capabilities, and high availability features. The choice between them depends on specific requirements, such as budget, control, application size, and analytical needs.
Considering moving part of our PostgreSQL database infrastructure to the cloud, however, not quite sure between AWS, Heroku, Azure and Google cloud. Things to consider: The main reason is for backing up and centralize all our data in the cloud. With that in mind the main elements are: -Pricing for storage. -Small team. -No need for high throughput. -Support for docker swarm and Kubernetes.
Good balance between easy to manage, pricing, docs and features.
DigitalOcean's offering is pretty solid. Easy to scale, great UI, automatic daily backups, decent pricing.
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
Pros of Heroku Postgres
- Easy to setup29
- Follower databases3
- Dataclips for sharing queries3
- Extremely reliable3
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Cons of Google Cloud SQL
Cons of Heroku Postgres
- Super expensive2