Google Cloud SQL

Have used Google Cloud SQL for e-commerce platforms handling transactions, inventory management, and customer data, Google Cloud SQL offers the reliability and scalability needed to support fluctuating traffic and ensure data integrity.Google Cloud SQL can be used as a backend database for analytics and reporting applications, providing fast access to large volumes of data for complex queries and data analysis.
It is not appropriate for non-supported database like oracle and also not good for migrating legacy systems. It cannot be used for real time data processing because it requires very low latency

Fully managed services with support for multiple database engines like PostgreSQL, MySql

Google Cloud SQL is a great primary database. It is certainly the first choice that any application developer should try while starting out with GCP. Unless there's an ultra-specific reason Google Cloud SQL should be choice for managed SQL databases.
Google Cloud SQL is not a proper choice for application which needs high or near real-time performance. Its not a good choice for distributed database applications either

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.

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.

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.

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.

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.

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.

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

Cons
- None I can think of

It is great if you don't want to worry about managing hardware and infrastructure and instead focus your efforts on work directly related to your product's database needs, i.e. schema design, efficient queries, etc. However, if you are dealing with very large data sets, then BigQuery, BigTable, or similar might be better suited for your needs.

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.

For a general purpose SQL database, it's very well suited, performant and secure, if you already use GCP.
If you intend to connect from other BI, analytics or 3rd party tools, I advise to check if they support SSL to Google Cloud SQL, because most don't. If you are on AWS, go with RDS

It is a very powerful database service. It can be easily set up even by an entry-level developer. It can be used by medium to large organizations in their various projects. It can be used by business apps as well at any level. It can also be used where latency is an issue as It is extremely fast

[Google Cloud SQL] is a big help for IT administrators to ensure the security of databases and data backups as well as replacing replica databases in failover situations, It is very powerful and fast in managing and migrating databases and it only takes a few minutes to create and connect to your first database using the built-in migration tools.

Overall, Cloud SQL serves all of the needs we need it to. It can do everything a relational database can do, plus it is completely managed so you don't have to worry about the size of the VM, partitioning, etc.

Google Cloud SQL was very easy to setup because our institution is already already invested in the Google Cloud Platform. If we had gone with Amazon or Azure, there would have been extra complexity and cost of getting established. The product is a great fit for organizations already invested in GCP. Google offers everything the others do, however third party vendor support is seriously lacking (aka the vendors refer you to other tools like AWS etc).

Google Cloud SQL is a great resource for some purposes, but it's probably overkill for others.
In cases where a database is not always needed (on sometimes, off others), it would be better to use a traditional software installation. If database needs are relatively small, software installation will perform just as well and be easier to support. If a database is only needed in one physical site or a small geographical region, it's better to use a regular server based installation. But as soon as a project has greater database needs, Google Cloud SQL is a great choice. Consider using it if any of these apply:

• A large amount of data (10+ GB).
• Decentralized access (many worksites, end-users, etc.).
• Uptime and reliability are required.

For any serious production setup, where "serious" means aware of the importance of having automatic/secure backups, a good recovery plan, high availability options and managed DB server maintenance, I go with this solution before any self-managed option.

I'd be cautious if I need too much processing power or storage available for my DB. On these cases, I'd first think again about my selected DB architecture, and then analyze some options to calculate ROI of each investment.

When you need relational storage.
Not when you need warehousing.

If you're hosting a site on Google Cloud, it only makes sense to make use of Google Cloud SQL for the database, as opposed to running a separate MySQL service on a VM. It's extremely fast and has resulted in a dramatic improvement in page load time across multiple sites.