Most companies are modernizing and moving into the cloud. While Developers and IT Organizations primarily use Google Cloud for secure and highly available object storage, Google now offers Database Service that makes it easy to set up, maintain, manage, and administer your Relational Databases in the cloud. Google Cloud SQL is a managed Google Cloud Database Service that handles administrative tasks such as Data Replication, Patch Management, and Database Management. This post will help you understand how you can leverage the Google Cloud MySQL connection to use Google Cloud’s Managed Database Service for MySQL Databases.
Organizations use structured Query Language (SQL) to manage and maintain Databases, and MySQL is one of the most widely used open-source Database Management Systems in the world. MySQL Server can store a huge amount of data in the form of MySQL tables. Google Cloud MySQL is a turnkey solution for deploying and running MySQL on Google Cloud, simplifying Database Management tasks like upgrades, configuration, and backups.
What is Google Cloud SQL?
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Google Cloud SQL is a fully-managed Google Cloud Database Service that manages and regulates Relational Databases on the Google Cloud Platform (GCP). It comes with an easy and quick setup and offers standard Connection Drivers and built-in Migration Tools. It automates Database Provisioning, Storage Capacity Management, Data Replication, and Backup, which in turn reduces maintenance costs. Enabling Automatic Storage Increase automatically adds more storage when nearing capacity.
Is your data safe in Google Cloud SQL? Well, your data in Cloud SQL gets full encryption at rest and in transit, just like anything else at Google Cloud. In addition to that, external connections can also be encrypted using SSL or Cloud SQL Proxy. Cloud SQL is a Relational Database, hence, it is best suited for Online Transactional Processing (OLTP) where frequent queries and fast response time are needed. Being a fully-managed setup, it is the provider’s responsibility to manage the databases, so you can focus on productivity and collaboration.
What is MySQL?
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MySQL is one of the most popular Relational Database Management Systems used for managing Relational Databases. MySQL uses the Structured Query Language (SQL) to define, update, and query the Database. SQL is the most widely used language for accessing and managing records in any Database. Supported by Oracle, MySQL is an open-source and free Database software under the GNU license.
MySQL is faster, highly scalable, and an easy-to-use Database Management System when compared to Microsoft SQL Server and Oracle Database. It is based on the Client-Server model, which means that the Database typically runs on a server and the data is accessed over the network part clients and workstations. The server returns the desired output to the Graphical User Interface (GUI) requests sent by the clients. MySQL supports different types of Operating Systems with many languages like PHP, PERL, JAVA, C++, C, etc.
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What is Google Cloud MySQL?
Google Cloud SQL for MySQL is a fully-managed database service for managing MySQL Databases. Using Google Cloud MySQL, customers can migrate their Databases without any downtime or data loss. It further allows you to deploy your operational workload data on the Google Cloud Platform in the right format.
With Google Cloud MySQL connector, you can access data from Cloud SQL for MySQL Databases within Data Studio. It offers a secure and scalable service for real-time data ingestion and supports all types of structured, semi-structured, and unstructured data in Cloud SQL Databases.
Google Cloud MySQL Key Features
Below are some of the benefits of the Google Cloud MySQL connection.
- You can create and manage SQL instances in the Google Cloud Platform.
- Google Cloud MySQL automates Data Replication between multiple zones with automatic failover. This means the Database instance will automatically failover to another zone in case of an outage.
- It allows you to import and export Databases using mysqldump. In addition to that, you can also import and export CSV files.
- You also get support for MySQL Wire Protocol and standard MySQL Connectors.
- Google Cloud MySQL connection supports automated and on-demand backups.
- You can continuously monitor your Data Pipelines in real time.
Google Cloud MySQL Pricing
The pricing of Google Cloud MySQL depends on the instances, storage, network, and data transfer. You can go through Google Cloud MySQL pricing details below.
Instance Pricing
You are charged every time a MySQL instance is launched. Usage charges depend on a lot of external factors as well, such as your machine type and the region in which the instance is located.
For a general understanding, you can have a look at the pricing in the US-Central region. In the US-Central region, every instance is charged starting from $0.0105 per hour for the smallest db-f1-micro instance, to $8.4504 per hour for the largest db-n1-highmem-96 instance with 96 vCPUs and 624 MB of RAM.
Storage Pricing
Similar to instance pricing, storage pricing for a MySQL instance also depends on the instance location. High Availability (HA) Storage is available at higher prices than Regular Storage.
| Type of Storage | Price Per GB/Month for HDD | Price Per GB/Month for SSD | Price Per GB/Month for Backups |
| Regular Storage | $0.090 | $0.170 | $0.080 |
| Highly Available (HA) Storage | $0.180 | $0.340 | $0.080 |
Storage PricingNetwork and Data Transfer Pricing
You are charged for exporting data to an external location from a network. However, you are not charged for serverless export in Google Cloud SQL. Below are the pricing details for network egress.
- Network egress within the same Google Cloud region or to other Google products in the same continent: Fee
- Network Egress to Google Compute Engine, Cloud SQL replicas in other regions, or other Google products in another continent: $0.12/GB
- Internet egress: $0.19/GB (this can be reduced to $0.05/GB if you’re using Google Cloud Interconnect)
Google Cloud MySQL Backup Management
As discussed in the introduction, Google Cloud MySQL makes it easy to manage backups and is capable of performing on-demand and automated backups. Managed backups can help you restore lost data to a Cloud SQL MySQL Database. There are two types of managed backups:
- On-Demand Backups: You can plan an on-demand backup at any time according to your needs. This is very useful in cases where you need an immediate backup to retain sensitive data. The backups are retained until you delete them.
- Automated Backups: Automated backups use a 4-hour window, and can start at any point during that window. The last 7 backups are retained automatically while the previous backups are discarded.
MySQL Replication Options
Google Cloud MySQL simplifies the Data Replication process with its 3 replication options:
- Read Replicas: A Read Replica represents an exact copy of the Master Instance, hence data changes to the Master Instance are reflected on Read Replicas in real-time. As the name suggests, Read Replicas are read-only, which means they can offload queries and read requests from the Master Instance. Google Cloud MySQL supports up to 10 read replicas for every MySQL Database.
- Cross-Region Read Replicas: As the name suggests, Cross-Region Replication allows you to create a Read Replica in a different region than the region in which your primary instance is located. Creating a replica in a different region makes the Database resilient to failures and uncertainties in the local region. This also allows you to migrate data between different regions with minimal downtime.
- External Read Replicas: An External Read Replica represents an external MySQL instance (such as MySQL instances running on Compute Engine) replicated from the Cloud SQL Master Instance.
Deployment of Google Cloud MySQL using
Fully-Managed
Features
- External Replica Migration and Promotion: This generates a replica of the on-premise database and synchronizes existing data with that copy. This can happen without downtime for production databases. Google Cloud SQL offers an automated migration workflow for this method, which can support migration from local databases or from other cloud providers.
- Import/Export Migration: This involves extracting data from your database using mysqldump, and then importing it to the hosted MySQL instance. This method needs downtime to ensure consistency.
Advantages
- If the team managing the database is not MySQL experts, or the requirements are basic, Google Cloud SQL is a great choice. Cloud SQL is a great solution for running and deploying MySQL, simplifying day-to-day operations and database administration tasks like configuration, upgrades, and backups.
Disadvantages
- Connection Limits: You can maintain up to 250, 1000, or 4000 simultaneous connections to the database, based on the instance size.
- Limit on Number of Instances: Google Cloud allows up to 40 database instances per project, by default. However, it is possible to request an increase on this limit from GCP support.
- Storage Limits: Supported databases can size up to 30.7 TB.
- No Access to the Server: You cannot directly access the database server and change the operating system, database configuration, or storage settings.
- Version Limitations: Only MySQL 5.7, 5.6, or 8.0 are currently supported. You cannot use other MySQL versions until Google makes them available.
- Difficult to Migrate: You can decide in which GCP region the database will run in, but it can be challenging to move to another GCP region, and you cannot easily migrate data to another cloud provider.
Self-Managed
Features
- Transfer Appliance: This refers to a Google-provided hardware appliance that can help you transfer large data volumes from your data center to Google Cloud, for MySQL databases with very large data volumes.
- Migrate for Compute Engine: Compute Engine allows you to perform fully-automated migration of workloads from on-premises bare-metal machines or VMs to Google Cloud.
Advantages
- No Version Limitations: You can run any version of MySQL on Compute Engine.
- No Limit on the number of Instances: You can run as many instances as needed, by starting more Compute Engine instances.
- No Storage Limits: You are only limited by the attached storage service, it is quite possible to use third-party services for large databases.
- Hybrid Data: It is easier to integrate your database with workloads and resources running on-premises or on other clouds.
- Maximum Flexibility: This defines the ability to customize everything from database settings to the environment.
- Cost Savings: It allows you to only pay for cloud resources you directly use, with no additional charges for premium management services.
- Advanced Database Features: These features allow you to tune database configuration to improve performance, gain better control over data replication, and leverage RAID for large-scale storage.
Disadvantages
- Expertise: The MySQL deployment needs to be managed by staff with extensive expertise in Google Cloud infrastructure and MySQL.
- Setup: Setting up MySQL and operating it day-to-day can be quite time-consuming.
- Maintenance: Your team is solely responsible for monitoring, backup, availability, replication, logging, and everything needed for an enterprise database deployment.
Fully-Managed vs. Self-Managed Deployment of Google Cloud MySQL
There are two ways of deploying MySQL on Google Cloud, one is a fully-managed option via Cloud SQL, and the other is a self-managed option via Compute Engine. The fully managed Google Cloud MySQL deployment is already talked about in the previous sections.
Google Compute Engine is an Infrastructure-as-a-service (IaaS) platform that provides excellent performance and reliability. The Compute Engine option is more suitable for enterprise-level requirements and experienced Database Administrators. It gives you a high level of control over your Google MySQL Database on GCP, allowing you to customize and configure the Database.
| Fully-managed MySQL Deployment | Self-managed MySQL Deployment |
| Google Cloud SQL allows up to 40 MySQL Database instances per project. | No limit on the number of instances, you can run as many Database instances as required. |
| GCP MySQL supports a Database size of up to 30.7TB. | There is no storage limit as such. |
| You can maintain up to 250, 1000, or 4000 concurrent connections to the Database. | There are no hard limits on the number of connections. |
| You can’t directly access the Database Server for modification and configuration. | You have the ability to customize and configure the Database Server settings. |
| It can be challenging to move from one GCP region to another, and you cannot easily migrate data to another Cloud Provider. | You can easily integrate or connect your Database with resources and workloads running on GCP or on other Clouds. |
| Google Cloud MySQL is best suited for basic requirements and doesn’t require any expertise. | MySQL deployment on Compute engine requires expertise in MySQL and Google Cloud to set up and maintain the Database. |
| Fully-managed GCP MySQL deployment supports only MySQL 8.0, 5.7, and 5.6. | Compute Engine allows you to run any version of MySQL on it. |
Fully-managed vs. Self-managed Google MySQL DeploymentHow to Connect to Cloud SQL for MySQL?
You can connect to Google Cloud MySQL Database via Data Studio. To do so, follow the below-mentioned steps.
- Sign in to Data Studio.
- From the top left, click on the “+” button to select a Data Source.
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- Select the “Cloud SQL for MySQL” connector.
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- You’ll be prompted to authorize Data Studio to access your data.
- Set up the connection to your Database.
- Click on “AUTHENTICATE”.
- You can now connect to a SQL Table from the list. You can also connect to a custom SQL query by selecting the “CUSTOM QUERY” option.
- Click on “CONNECT”.
You’ve now successfully established a connection for Google Cloud MySQL.
Conclusion
With every organization moving most of its business into the cloud, it is essential to keep improving the performance of your applications while keeping your costs low. Google Cloud MySQL is a fully-managed Database Service that lets you hand off mundane, time-consuming tasks, like patches, backups, and replicas. This saves you valuable time and helps you to focus on building your app!
However, migrating massive amounts of data from MySQL to a Cloud SQL is a tedious and time taking process but using a Data Integration tool like Hevo can perform this process with no effort and no time. If you have existing Databases running in MySQL, you can conveniently shift them to Google Cloud SQL with Hevo Data.
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Share your experience of working with Google Cloud MySQL in the comments section below.