Item: Google Cloud SQL
Rating: 9
Author: Hemant Chaturvedi

Use Cases and Deployment Scope

Google Cloud SQL is a robust cloud-based SQL platform that we use at our organization to maintain our data. It is an exceptionally responsive, scalable, highly available, and reliable database platform. We use this platform for all the SQL requirements, including storing, querying, modifying, maintaining, and analyzing targeted data, which helps uncover helpful use cases and adds value to our organization. Since it is highly available, we hardly see any downtime, and even if there is any regional downtime, the service runs continuously from other geographies, thanks to the disaster recovery models at work in the backend. Our organization is a proud user of the GCP services and Google Cloud SQL platform.

Pros and Cons

Highly scalable without worrying about sudden transaction explosion during peak hours.
Highly available with multiple geographical locations and regions for nearly 0 downtime to the users.
Extremely reliable and responsive for high latency applications due to superb networking at the core.

Database snapshot cost-effectiveness can be improved to give it an edge over other cost-effective solutions for the same purpose.

Return on Investment

I switched from AWS RDS to GCP Cloud SQL for cloud-based SQL and improved ROI by 15% along with improved database availability.
Automated repetitive work via GCP's automated querying and triggering capabilities closed nearly 23% more tasks than a manual DB Administration and cleanup approach.

Usability

Google Cloud SQL is similar to the long existing conventional DBs like Oracle RDBMS, MS SQL Server in terms of usability and much more robust and easy to manage than them. Most of the commands are almost identical to these DB platforms and thus, easy to learn, understand and start using.

Also, being highly available, it brings a sense of reliability with Google Cloud SQL.

Ease of Integration

Although Google is the newest among the top 3 cloud service providers (AWS, Azure and GCP), it has shown tremendous integration capabilities surpassing even the other two in many ways.

Options of integrating it with almost all other popular platforms and services via its APIs is super easy. One can achieve this via the API page or using CloudShell in the GCP console.

Alternatives Considered

Azure SQL Database, Azure SQL Managed Instance and Amazon Relational Database Service (RDS)

It is cheaper than other cloud giants for the minimum instances and upfront capital investment requirement. It offers decent pricing for long-term usage on moderate or even high-spec instances (comparable to AWS and far better than Azure). Many more available resources are deployed worldwide than other cloud giants combined, and one can see that based on the availability of applications and resources, especially in 2023 when multiple outages were experienced where other cloud giants were managing the backend.

Key Insights

Do you think Google Cloud SQL delivers good value for the price?

Yes

Are you happy with Google Cloud SQL's feature set?

Yes

Did Google Cloud SQL live up to sales and marketing promises?

I wasn't involved with the selection/purchase process

Did implementation of Google Cloud SQL go as expected?

Yes

Would you buy Google Cloud SQL again?

Yes

Other Software Used

Microsoft Power BI, Python IDLE, Microsoft Visual Studio Code, Microsoft Power Automate

Likelihood to Recommend

An ideal choice for use cases mentioned below: Mission-critical applications with the criticality of nearly always on or always on. Robust and responsive database backend for elastic resources working behind. Low latency and high transaction-demanding applications.

Google Cloud SQL: The clear winner.

Overall Satisfaction with Google Cloud SQL