Google Cloud SQL is a fully-managed database service that stands out from its competitors due to its high performance, seamless integration, and impressive scalability.
This blog post covers everything about Google Cloud SQL like its features, benefits, use-cases, and three types of database engine supported by it.
Cloud SQL Overview
Google Cloud SQL offers the flexibility to set up database infrastructure once done with cloud application development. If you have existing databases running in MySQL, SQL Server, or PostgreSQL BETA, you can conveniently shift them to Cloud SQL. It is a database service providing by Google. To know more about other database services read the blog at Google Cloud Storage & Database Services.
Let’s understand the terms fully managed and Relational Database in detail:
1. Fully-Managed
In a fully-managed setup, the business pays fees to the provider and gains access to the database infrastructure. It is the provider’s responsibility to manage the databases. With the fully-managed database service, the business can focus on productivity and collaboration while scaling its applications.
2. Relational Database
A relational database is a type of database management system that stores related data. The database is established in the form of rows and tables which contain interrelated data items.
The characteristics of a relational database include:
- Structured Query Language (SQL): This is a primary interface that helps build communication with relational databases. It can be used to add, update, delete, and extract data or subsets of data as and when required.
- Data Integrity: Relational databases maintain accuracy, consistency, and completeness of data.
Features of Google Cloud SQL
The features of Google Cloud SQL are manifold. Some of which include:
1. Less Maintenance Cost
Being attributed as fully-managed, users do not have to worry about the maintenance of the application data. This gives them the flexibility to focus on improving their cloud applications.
2. Ensure Business Continuity
Cloud SQL ensures data backup and recovery i.e., in case of any disaster, users can easily retrieve the application data and continue operations without worrying about interruptions.
3. Ensures Security and Compliance
It provides data encryption and firewall protection. Cloud SQL is a secure RDBMS service focusing on providing private connectivity through authentication and user-controlled network access.
4. Easy-Setup
The standard connection drivers and migration tools enable users to set up their first Google database app within minutes. Google’s easy-to-use SQL service provides a hassle-free first-time experience.
5. Automated Tasks
Cloud SQL supports automatic task management to ensure you can focus on scaling your business on the go. Whether it is storage management, backup or redundancy management, undergoing updates, capacity management, or providing data access, the Google service offers it all.
6. Easy Integration
Google provides easy access to cloud SQL instances and ensures easy integration with Kubernetes Engine, App Engine, and Compute Engine. It also helps in building analytics possibilities and allows users to make SQL queries to the databases through BigQuery.
7. Easy Migration
Database Migration Service (DMS) makes it easier to migrate the production databases to Cloud SQL with minimal downtime. It eliminates the manual hassle of provisioning, managing, and monitoring migration-specific resources. It leverages the native replication capabilities of MySQL and PostgreSQL to maximize the fidelity and reliability of the migration and it’s available at no additional charge for native like-to-like migrations to Cloud SQL.
8. Cloud SQL Insights
It helps to quickly understand and resolve database performance issues on Cloud SQL.
Use-Cases
Google Cloud SQL provides a cloud-based alternative to local MySQL, PostgreSQL, and SQL Server databases. Users should use Cloud SQL if they want to spend less time managing their database and more time using it.
Many applications running on Compute Engine, App Engine, and other services in Google Cloud use Cloud SQL for database storage.
One of the most common use cases is:
1.) Build a containerized app with a scalable database
Google Kubernetes Engine enables rapid development by making it easy to deploy, update, and manage applications and services. Cloud SQL makes it easy to set up, manage, and administer Postgres databases on Google Cloud. This use case is a building block of a microservices architecture that is backed by an independent storage service, decentralizing data management and ensuring that each service is independently scalable.
Relational Database Engines Supported By Cloud SQL
The three relational database engines supported by Google Cloud SQL include:
1.) MySQL
It is an open-source, fully-managed, relational database management system used for cloud application development and deployment.
You can use Cloud SQL for MySQL with App Engine applications that are written in languages specifically Java, Python, PHP, Node.js, Go, and Ruby. Cloud SQL for MySQL can also be used with external applications using the standard MySQL protocol.
Features of Cloud SQL for MySQL
- Fully managed MySQL Community Edition databases in the cloud.
- Create and manage instances in the Google Cloud Console.
- Instances are available in the US, EU, Asia, and Australia.
- Customer data is encrypted on Google’s internal networks and also in database tables, temporary files, and backups.
- Supports Automated and on-demand backups, and point-in-time recovery.
- Allows Integration with Google Cloud’s operations suite logging and monitoring.
2.) PostgreSQL
PostgreSQL is a free, open-source, advanced RDBMS that can handle web services supporting many users at the same time. It focuses on extensibility and is referred to as enterprise-class RDBMS.
Cloud SQL for PostgreSQL can be used with App Engine applications running in a flexible environment written in Java, Python, PHP, Node.js, Go, and Ruby. It can also be used with external applications using the standard PostgreSQL client-server protocol.
Features of Cloud SQL for PostgreSQL
- Fully managed PostgreSQL databases in the cloud.
- Provides custom machine types with up to 624 GB of RAM and 96 CPUs.
- Up to 30 TB of storage available, which can be expanded if needed
- Provides data replication between multiple zones with automatic failover.
- Support for PostgreSQL client-server protocol and standard PostgreSQL connectors.
3.) SQL Server
SQL Server is a relational database management software product that helps store and extract data when requested by the applications which can be running on the same system or a network of systems spread across a network.
Users can use Cloud SQL for SQL Server with App Engine applications running in the flexible environment written in Java, Python, PHP, Node.js, Go, and Ruby.
Features of Cloud SQL for SQL Server
- Fully managed SQL Server databases in the cloud.
- Up to 30 TB of storage available which also provides the ability to automatically increase the storage size if needed.
- Support for secure external connections with the Cloud SQL Auth proxy or with the SSL/TLS protocol.
- Allows integration with Stackdriver logging and monitoring.
- Provides high availability through the regional persistent disk.
Key Terminology Related To Google Cloud SQL
1.) Cloud SQL Instance: It corresponds to one virtual machine (VM). The VM includes the database instance and accompanying software containers to keep the database instance up and running.
2.) Database Instance: A database instance is the set of software and files that operate the databases.
3.) High Availability: Cloud SQL instances using high availability (HA) provide greater reliability than non-HA instances. HA in Cloud SQL works by having two synchronized instances: a primary instance and a standby instance. Each instance has exactly one VM. Each instance is in a different zone in the same region.
4.) Failover: A failover is when Cloud SQL switches serving from the original primary instance to the standby instance.
5.) Replication: Replication is the ability to create copies of a Cloud SQL instance or an on-premises database, and offload work to the copies. This is processed to scale the use of data in a database without degrading performance on the primary instance.
6.) Read Replica: It is an exact copy of the primary instance. Data and other changes on the primary instance are updated in almost real-time on the read replica. The read replica processes queries, read requests, and analytics traffic, which in result reduces the load on the primary instance.
Frequently Asked Questions
1.) Who can access the data in Google Cloud SQL?
Answer: Instance-level access authorizes access to the Cloud SQL instance from an application or client (running on App Engine or externally) or from another Google Cloud service, such as Compute Engine.
2.) What is the best MySQL tool to use for managing the instance?
Answer: There are a variety of MySQL tools available for Cloud SQL.
- MySQL Command-Line Tool: for executing individual statements.
- Toad for MySQL or MySQL Workbench: to execute complicated tasks or to use a rich database development environment.
Related References
- GCP Associate Cloud Engineer: All You Need To Know About
- Google Associate Cloud Engineer: Step-by-Step Hands-On
- Google Cloud Free Account: Steps to Register for Free-trial Account
- Introduction To Google Cloud Platform
- Google Cloud Services & Tools
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