Google Cloud SQL

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 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.

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 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.

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.

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.

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.

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.

We are using Google Cloud SQL as a managed service for R&D. We wanted to focus on the data without the need to manage the updates or security patches. We also wanted to have the ability to spin up SQL fast without going through the purchasing process--just click and it works.

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 migrated from using on-prem SQL databases to Google's managed MySQL database, CloudSQL, a few years back. It supports all of our relational database needs. Along with other Google-managed data structures, Cloud SQL plays an integral role for our software team and our R&D teams, as it is used as the primary storage for company-wide analysis.

We came to Google Cloud SQL in need of a cloud database solution to house analytic data we collect from various I.T. systems, most importantly our trouble ticketing tool. The goal was a central repository that was easy to manage for our small organization. Our data storage needs are small compared to many organizations.

We use Google Cloud SQL for databases that are accessed across multiple servers. These dedicated SQL instances are easy to set up since they don't require a host VM. Not requiring a host VM also allows them to be more flexible and scalable. Settings allow Google Cloud SQL instances to automatically scale size as storage needs increase, and perform scheduled maintenance and backup. In our experience scaling and maintenance do not impact any system functionality.

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)

[We're] using it as the primary database supporting multiple WordPress installations that are running on Google Cloud. It's being used for every site that we currently have on Google Cloud, and are in the process of moving more sites over to this platform. Having everything on Google's infrastructure makes everything easy to manage and Google Cloud SQL is insanely fast.