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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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

Advice on Google Cloud SQL and Heroku Postgres

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.

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Replies (2)
David Weinberg

Good balance between easy to manage, pricing, docs and features.

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Max Musing
Founder & CEO at BaseDash · | 1 upvotes · 45.4K views

DigitalOcean's offering is pretty solid. Easy to scale, great UI, automatic daily backups, decent pricing.

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Pros of Google Cloud SQL
Pros of Heroku Postgres
  • 13
    Fully managed
  • 10
    Backed by Google
  • 10
    SQL
  • 4
    Flexible
  • 3
    Encryption at rest and transit
  • 3
    Automatic Software Patching
  • 3
    Replication across multiple zone by default
  • 29
    Easy to setup
  • 3
    Follower databases
  • 3
    Dataclips for sharing queries
  • 3
    Extremely reliable

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Cons of Google Cloud SQL
Cons of Heroku Postgres
    Be the first to leave a con
    • 2
      Super expensive

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    What is Google Cloud SQL?

    Run the same relational databases you know with their rich extension collections, configuration flags and developer ecosystem, but without the hassle of self management.

    What is Heroku Postgres?

    Heroku Postgres provides a SQL database-as-a-service that lets you focus on building your application instead of messing around with database management.

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    What companies use Google Cloud SQL?
    What companies use Heroku Postgres?
    See which teams inside your own company are using Google Cloud SQL or Heroku Postgres.
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    What tools integrate with Google Cloud SQL?
    What tools integrate with Heroku Postgres?

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    What are some alternatives to Google Cloud SQL and Heroku Postgres?
    MySQL
    The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
    Apache Aurora
    Apache Aurora is a service scheduler that runs on top of Mesos, enabling you to run long-running services that take advantage of Mesos' scalability, fault-tolerance, and resource isolation.
    Google Cloud Datastore
    Use a managed, NoSQL, schemaless database for storing non-relational data. Cloud Datastore automatically scales as you need it and supports transactions as well as robust, SQL-like queries.
    Google Cloud Spanner
    It is a globally distributed database service that gives developers a production-ready storage solution. It provides key features such as global transactions, strongly consistent reads, and automatic multi-site replication and failover.
    PostgreSQL
    PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
    See all alternatives