Overview
What is Google Cloud SQL?
Google Cloud SQL is a database-as-a-service (DBaaS) with the capability and functionality of MySQL.
Unlocking the Power of Cloud Databases: A Comprehensive Review of Google Cloud SQL
The Default GCP database
Google Cloud SQL - Great Database for Your App
Google Cloud SQL: The clear winner.
A good solution for early developing & scaling through growth.
Google Cloud SQL as a Database as a Service.
Google Cloud SQL is the best database management service tool
Best SQL in market is Google Cloud SQL, hands down!
Effortless Database Management: A Review of Google Cloud SQL
Great cloud db offering
Google Cloud SQL is best SQL offering for relational database
SQL management for everyone
Complete and works very well with GCP
Google Cloud SQL: Fully managed and secure SQL service
Awards
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Popular Features
- Automated backups (23)9.494%
- Database security provisions (23)9.292%
- Database scalability (23)9.090%
- Monitoring and metrics (22)8.686%
Reviewer Pros & Cons
Pricing
License - Express
$0
License - Web
$0.01134
Storage - for backups
$.08
Entry-level set up fee?
- No setup fee
Offerings
- Free Trial
- Free/Freemium Version
- Premium Consulting/Integration Services
Product Demos
Choosing a PostgreSQL database on Google Cloud
Database Configurations with Google Cloud SQL
Connecting Google Sheets to Cloud SQL using Apps Script
Features
Database-as-a-Service
Database as a Service (DBaaS) software, sometimes referred to as cloud database software, is the delivery of database services ocer the Internet as a service
- 9.6Automatic software patching(12) Ratings
Patches applied to database automatically
- 9Database scalability(23) Ratings
Ease of scaling compute or memory resources and storage up or down
- 9.4Automated backups(23) Ratings
Automated backup enabling point-in-time data recovery
- 9.2Database security provisions(23) Ratings
Provision for database encryption, network isolation, and identity access management
- 8.6Monitoring and metrics(22) Ratings
Built-in monitoring of multiple operational metrics
- 9Automatic host deployment(12) Ratings
Compute instance replacement in the event of hardware failure
Product Details
- About
- Competitors
- Tech Details
- FAQs
What is Google Cloud SQL?
Fully managed
Cloud SQL automates backups, replication, patches, encryption, and storage capacity.
Open and standards-based
Cloud SQL supports the most popular open source and commercial engines, including MySQL, PostgreSQL, and SQL Server with support for extensions, configuration flags, and popular developer tools. The user can create a database with a few clicks in the console and connect an application.
Cost-effectiveness
Users can scale with application growth, customize machine types, and choose different levels of performance and availability, up to a 99.99% availability SLA. Committed use discounts offer additional savings for one to three year commitments.
Intelligent insights and manageability
Gemini in Databases
AI-powered assistance is included to simplify database management. Gemini in Cloud SQL, in preview, enables developers, operators, and database administrators to build applications quickly using natural language, and helps manage, optimize, and govern an entire fleet of databases with a single pane of glass.
Google Cloud SQL Features
Database-as-a-Service Features
- Supported: Database scalability
- Supported: Automated backups
- Supported: Database security provisions
- Supported: Monitoring and metrics
Google Cloud SQL Screenshots
Google Cloud SQL Videos
Google Cloud SQL Competitors
Google Cloud SQL Technical Details
Deployment Types | Software as a Service (SaaS), Cloud, or Web-Based |
---|---|
Operating Systems | Unspecified |
Mobile Application | No |
Frequently Asked Questions
Comparisons
Compare with
Reviews and Ratings
(80)Attribute Ratings
Reviews
(1-23 of 23)Fantastic product !!!
- Minimizes downtime and data loss risks.
- Built-in encryption and access controls simplifies data protection.
- It adjusts resources as required, maintaining performance without manual adjustment.
- Cost can be improved. Improved cost transparency tools would help users manages expenses more efficiently.
- Enhanced analytics and diagnostics could aid proactive and maintenance and optimization efforts.
- It does not integrate easily outside google ecosystem.
- easy setup and monitoring
- easy migration with network connectivity
- easy export and import of data
- Google Cloud SQL's performance might not always match that of a dedicated, self-managed database server, especially in scenarios with high throughput or complex queries.
- Cost also needs to be reduced currently it is little expensive
- Has to add more support of databases.While Google Cloud SQL supports popular database engines like MySQL, PostgreSQL, and SQL Server, it may not support other specialized databases for eg Oracle
The Default GCP database
- Migration
- The Database Migration Service has excellent throughput and supports virtually unlimited amount of data.
- Insights
- The Cloud Insights dashboard is a great place to analyse query performance and resolve database performance issues through pre-built dashboards.
- Excellent Dialects
- Google Cloud SQL supports a lot of open-source dialects including MySQL, PostgreSQL and SQL server
- No access to the databases logs
- System stored procedures are not accessible
- Data is not automatically encrypted in transit though Google does AES encryption at rest
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
Google Cloud SQL - Great Database for Your App
- Autoscaling storage
- Ease of use to scale up vertically when needed
- High availability database
- If storage that has been auto-scaled, it would be great if it can be shrunk to reduced cost
- Auto sizing in Google Cloud SQL without downtime
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.
Google Cloud SQL: The clear winner.
- Highly scalable without worrying about sudden transaction explosion during peak hours.
- Highly available with multiple geographical locations and regions for nearly 0 downtime to the users.
- Extremely reliable and responsive for high latency applications due to superb networking at the core.
- Database snapshot cost-effectiveness can be improved to give it an edge over other cost-effective solutions for the same purpose.
- Secure connections.
- Easy to scale.
- Easy to maintain.
- A desktop management application could be useful.
- A better split between the way service accounts are created by users and have it designated separately to the rest of workspace.
- Improved alerting with third party monitoring.
Google Cloud SQL as a Database as a Service.
- Providing Free trial of 300 dollars.
- Better monitoring capabilities and troubleshooting features.
- Easier to set up an instance.
- Lag of releasing the new open-source database systems for Google Cloud SQL.
- Not much efficient and advanced billing cycle system.
- Not having much rich database visualization / dashboards.
- Automated Tasks
- Manage and administer Relational Databases
- Easy Migration
- More Documentation
- Product cost can reduced
- Better Integration with other BI Tools
Best SQL in market is Google Cloud SQL, hands down!
- It supports MySQL, PostgreSQL
- It has high availability
- It has vertical and horizontal scaling
- Increasing support for more database engines may enable a wider range of application needs to be met.
- Implementing and updating cutting-edge security features on a constant basis.
- Streamlining and enhancing the tools for transferring data to Google Cloud SQL from on-premises databases or other cloud providers.
- Handle Transactions
- MIS & Reporting
- Maintain Structured Datasets
- Better Control over ACL
- Add replication factor to have a Readonly Reporting DB
- Great for storing Structured dataset
- Handling Transaction based workflows
Cons
- None I can think of
Great cloud db offering
- Automatic failover to another region in case the database goes down.
- Easily scale the instance up if more processing power or memory is required.
- Automatic backup validation. The backups are performed on a daily basis within the selected window, however, they are not validated. This means the backup could be reported as successful but ultimately be unusable in a situation where it is needed. We got around this issue by periodically validating on our own by spinning up a box, restoring the backup to the new instance, and then destroying the instance after validation. It's not perfect, but is a good sanity check to make sure our backups are valid in case we do need them.
Google Cloud SQL is best SQL offering for relational database
- Scalability
- Read only replicas
- Easy migration
- Partitioning
- Golden gate type of replication
- Recovery mechanism
But, I guess it would not be useful for IoT, analytics, real-time processing of data, etc. Where big data is more prominent.
SQL management for everyone
- Spins up fast
- Easy to apply
- No need to purchase licenses in advance
- Unsupported external tools to monitor MSSQL
- Latency from working outside Google Cloud environment
- There some preferences you cannot edit/customize
- Any company/team that needs/wants to grow fast will find that Google Cloud SQL will suit them well.
- Pay-as-you-go option and saving you time for implementing infrastructure for SQL solution are big advantage.
- The agility to spin up a database in any region and move it if needed.
Complete and works very well with GCP
It supports high availability and read replicas, as Pitr backup recovery and logs/metrics integrated to Google Cloud monitoring.
- Pitr backups
- High availability
- Read replicas
- Log and monitoring
- SSL certificates are self signed, most services dont support them
- Cant query high availability replicas [in my experience]
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 fully managed
- It is easy to setup
- It provides high speed data transfer
- [I feel] It needs more integrations
- [I feel it] Needs to work on price structure
- High security and agility in query databases
- Multi-platform and database recovery capability with just one click
- Possibility of automatic switch to replica database in failover situations
- Simple built in migration and connection tools
- Many areas, including caching and indexing data, need to be developed
- Create snapshot option of instance
- The dashboard and monitoring section can have better customization capabilities
Brilliant for data storage, processing, and analysis
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
- Very easy to use and migrate existing database systems to Google Cloud SQL system
- Easy to query with real-time query assessment as well as processing metrics to help optimize the queries
- No need to learn any other querying language (like in Hadoop ecosystem), as SQL works pretty fine
- Easy-to-use GCP portal to type in queries and see the results on the screen (no need to go on command line )
- Easy to set up
- Lack of latency with quota size increasing
- Can't customize an instance’s IP
- Bit more expensive than some other players in the market, for instance, while downloading information
- Well suited for relational database storage and connections
- Supports well-built APIs, which ensures easy access
- Automatic failover (moving an application to a standby Google Cloud SQL server in case an instance fails)
- Works really well with other Google Cloud products like Compute Engine, AppEngine, Kubernetes, etc.
- Ensures security and compliance
All the functionality of MySQL with added managed support
- It is fully managed, so it gives the user a hands-off approach to relational storage.
- It has well-built APIs, so it is easy to access in a multitude of ways.
- It is reasonably easy to use with the Google Cloud Console, so users can access it using a user interface.
- There is some functionality you cannot do from the console, including, granting and restricting user privileges, among other database management capabilities.
- It is not trivial to connect to spun up VMS. Currently, we use the Cloud SQL proxy to do so.
- Easy Setup
- Easy Configuration
- Tools we use send people elsewhere (AWS especially)
- Few integrations
Simpler and more reliable database hosting
- Easy setup - No host VM, no software installation or configuration required.
- Day to day reliability - Not depending on host VM allows more uptime.
- Long term reliability - Storage scaling, backups, and maintenance can be scheduled to occur automatically.
- Secure access is complicated to set up - This is the nature of secure access, but it can be frustrating spending much time simply configuring access.
- No custom IP - It isn't possible to customize an instance's IP. This makes it harder to replace an instance since a new or clone instance always gets a new IP.
- Cost tends to increase - This is the nature of cloud hosting, but over time costs creep up as utilization increases.
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.
Managed MySQL/PostgreSQL DB infrastructure and clusters
- Configuring a high availability cluster of MySQL or PostgreSQL databases is as easy as choosing how many instances do you want to have. Read-only replicas of the master DB can also be used for read operations relying on the "almost instant" replication mechanisms available.
- Plays really well with other Google Cloud products, so interoperation with Cloud Functions, Cloud Run, Compute Engine, AppEngine, Kubernetes, VPC, etc. is straightforward and easy to secure, isolating the systems from outside.
- Uptime SLA is high and maintenance operations are planned and notified in anticipation. Network and CPU performance is really good.
- Automatic failover on high availability setups will automatically promote a read replica to master almost transparently for the client, so our applications will keep running even if the master DB server crashes.
- There are no multi-master replication options. That may be a problem on distributed, high load, high performance environments.
- Not many DB vendors available. MySQL came first, PostgreSQL took longer to be available and just now SQL Server is being offered as Beta.
- Can get pricey quickly if you need to grow fast and much.
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.
Google Cloud SQL Review from a daily user
Use case:
- Historical pricing of products (Archive)
- Super easy to set up: new instance -> Authorization -> play
- Automatic backup every night! (Keeps past 7 days as copy as well)
- Automatic failover, in case your main SQL instance fails, they automatically switch you over.
- It could be cheaper. Definitely cheaper.
- It could provide more information about failovers.
- It could allow you to customize more.
Not when you need warehousing.
Google Cloud SQL is Crazy Fast
- It's insanely fast.
- Easy integration with Google Cloud hosted services.
- It's backed by Google's infrastructure, which is always good.
- Connecting to it for the first time is a little confusing.
- An interface for interacting with the data would be awesome.