Google Cloud SQL Reviews & Insights

In our organization we need to store a large amount of data that is very efficient to access. For this reason we need a managed relational database that is easy to scale and manage.

It's definitely suited for companies that needs a very efficient and performant database with the option to scale the server based on needs.

We use Google Cloud SQL as our primary production Postgres database, as well as our development/staging database. We love it because of its autoscaling features, automated backups, and excellent security. We primarily connect to the database via our Google Cloud Run instance, and it's all securely tied down in a VPC. It also serves well as a development/staging database - we just turn off some of the more premium features like autoscaling.

Google Cloud SQL works perfectly as a production database - it's really got all the features you'd want to have good production-related practices and it stays affordable via autoscaling. It probably would be overkill as a development/staging database, but it's also nice to reuse the same configuration between them.

I am working on a e-commerce website and has to use 2 databases one for transactions for this I used Google Cloud SQL and other I use nosql db.The Google Cloud SQL is easy to setup it is basically a plug and play kind of system.Earlier I am using aws rds has to shift to Google Cloud SQL and used google data migration service for this.

I used Google Cloud SQL in my previous organization to be database of apps that we developed such as safety management system in mining, workflow management system developed in-house, supplier management system, microservices for various apps in subsidiary company e.g. insurtech, crypto, media, fintech, and many others. At that time, I found no issue using Google Cloud SQL.

It is suited for application that requires relational database where relationship between table must be strict and database has to support join and transaction e.g. if a DML statement fails within a transaction the previously successful statement must be rolled-back, like finance app, supply chain, transaction app, etc.

It is not suited for application where data definition can't be defined in advance like NoSQL. And also not suited to contain cache for apps and receiving big amount of data (e.g. sensor) in short time.

Google Cloud SQL was used to enable a number of our public cloud applications to centrally store and access data quickly, efficiently and in a secure way. It is often difficult to find a good SQL provider and this worked well for us, enabling easy migration and scaling of our applications.

GCSQL is great as a starter SQL provision for when building and developing. It has limitations when really trying to scale and with larger teams, but seems fine for individual developers or smaller apps & orgs that need something easy and quick, mostly following an enterprise style. Ideally, this works well with fully cloud applications.

Google Cloud SQL was mainly used to create interesting websites for many customers, who are middle-scale companies and individuals. We also used Cloud SQL products to create and manage virtual machines that can be used for training purposes for interns and newcomers so they can try out our developments.

Although Google Cloud SQL has room for improvement by addressing a minor lack of features, its features and services keep it high among other SQL database products. It is very fast compared to others. Since it is cloud-based, maintenance is also easier. Integration capabilities are also more than expected.

We use Google Cloud SQL to manage relational databases in our organization on cloud. It helps us to setup and administer our relational databases with less human intervention. It automates all our backups, encryptions, increase storage capacity to provide our application reliability and scalability.

If you have a large relational database and you want to migrate it to cloud then Google Cloud SQL is best suited for it. It helps you to automate lot of tasks. You should use Google Cloud SQL if you want less time to manage database and spend more time using it.

We use programming languages or common SQL clients to establish a connection with the instance. We use the given interfaces to administer the database and run SQL queries. It frees us from worrying as much about the supporting infrastructure and lets us concentrate more on developing apps. Additionally, it enables read replicas, which lets us transfer read queries to replicas for faster processing.

A great option for web application backend powering is Google Cloud SQL. Google Cloud SQL can be used by online retailers and e-commerce platforms that need a dependable and scalable database backbone. Using Google Cloud SQL, our developers can quickly spin up database instances without requiring a lot of setup or maintenance. This fully-managed service is available for both development and testing environments.

We use Google Cloud SQL with Mysql Engine as the primary Database for storing Application Data. Our compute engine are connected to the SQL Cloud. We also use it to store the summarised data for MIS & Reporting.

Pros
- Great for storing Structured dataset
- Handling Transaction based workflows

Cons
- None I can think of

Google Cloud SQL is being used by our organization at the enterprise level. It's being used in different projects. In some projects, we have migrated SQL DB to cloud SQL DB to save cost and leverage scalability. It's really easy to migrate data from on-premise to cloud SQL and use ETL also.

Best suited for Financial services, banks, eCommerce, telecom companies products where more relational database kind of data is required and where we want to migrate from legacy system to cloud world.
But, I guess it would not be useful for IoT, analytics, real-time processing of data, etc. Where big data is more prominent.