Google Cloud SQL

Google Cloud SQL provides a DB on cloud for my org. We use Google Cloud SQL for all DB related operations and we use postgre SQL as underlying RDBMS on google cloud SQL that can create Replicas and provide multi region data backup. It is fast and reliable to use so far we have not encountered any unwanted downtimes and connectivity or latency issues at all , over all it fulfills all that is required for any big MNC.

We used postage SQL to host our relational data of product catalog. Initially we had custom PostgreSQL hosted on AWS but due to costing, scalability and overhead of managing the underlying infrastructure we decided to move to some cloud hosted fully managed database. After evaluation we decided to choose GCP (Google Cloud Platform) and we have GCP hosted PostgreSQL.

Google Cloud SQL is the managed database solution in GCP. Google Cloud SQL usage is extensive in our organization and almost all applications using flavours of postgres sql and MySQL use Google Cloud SQL. Google Cloud SQL is our primary database of choice on migrating applications to Google cloud and its generally our main backup db as well. Its single biggest strength is flexiblity with the databse being useful both as a prototyping solution and a production solutions

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.

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.

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.

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.

Google Cloud SQL (MySQL) is used as the relational data store for our product. The ability to scale up, have read replicas, and have automatic failover built into the offering are really nice features. The automated backup feature is nice as well. To have 7 days of backups available at any time without having to support the processes necessary to make that happen is great.

We use it as the main SQL database for our SaaS. The server is hosted on Cloud Run (serverless) and connect direcly using private IP inside the VPC.
It supports high availability and read replicas, as Pitr backup recovery and logs/metrics integrated to Google Cloud monitoring.

I have worked with Google Cloud SQL for a R&D project. I was given the task to implement a data conversion application. we wanted to migrate from an on-prem SQL database to Google Cloud SQL. we decided to use Google SQL. It supports all the relational database needs. It is a fully managed and secure service.

We use Google Cloud SQL in all web projects to increase security and reliable backup. When any errors in the initial database are interrupted or occurred, the system switches to the replica db version according to the settings already defined for it, so that users can access the site and platform or application DB information. As a SAAS platform, it has excellent monitoring capabilities, multi-platform, high security, and agility in queries, and ultra-fast data analysis and the Google support team is very responsive.

Google Cloud SQL is used across technology, analytics and BI teams to store relational databases, tables, and run queries to fetch data from these databases.

Business problems addressed:

• Joining data tables from different databases to give a combined view of attributes and records
• Run SQL queries to fetch raw data and prepare product usage reports on top of it
• Prepare an automated data API workflow to be sent directly to BI systems to generate automatic reports

We use Google Cloud SQL with MySQL instances as our primary data storage for all our applications. Performance is great and configuring secure environments is straightforward. We reduced our DB maintenance tasks by 75% and our systems are running better than ever. Automatic backup policies and high availability replication are 1 click away.

We have been using it mainly whenever we need structured data.

Use case:
- Historical pricing of products (Archive)