Google Cloud SQL is a database-as-a-service (DBaaS) with the capability and functionality of MySQL.
$0
per core hour
IBM Cloud Databases
Score 8.1 out of 10
N/A
IBM Cloud Databases are open source data stores for enterprise application development. Built on a Kubernetes foundation, they offer a database platform for serverless applications. They are designed to scale storage and compute resources seamlessly without being constrained by the limits of a single server. Natively integrated and available in the IBM Cloud console, these databases are now available through a consistent consumption, pricing, and interaction model. They aim to provide a cohesive…
N/A
Azure SQL Database
Score 8.4 out of 10
N/A
Azure SQL Database is Microsoft's relational database as a service (DBaaS).
$0.50
Per Hour
Pricing
Google Cloud SQL
IBM Cloud Databases
Azure SQL Database
Editions & Modules
License - Express
$0
per core hour
License - Web
$0.01134
per core hour
Storage - for backups
$.08
per month per GB
HA Storage - for backups
$.08
per month per GB
Storage - HDD storage capacity
$.09
per month per GB
License - Standard
$0.13
per core hour
Storage - SSD storage capacity
$.17
per month per GB
HA Storage - HDD storage capacity
$.18
per month per GB
HA Storage - SSD storage capacity
$.34
per month per GB
License - Enterprise
$0.47
per core hour
Memory
$5.11
per month per GB
HA Memory
$10.22
per month per GB
vCPUs
$30.15
per month per vCPU
HA vCPUs
$60.30
per month per vCPU
No answers on this topic
2 vCORE
$0.5044
Per Hour
6 vCORE
$1.5131
Per Hour
10 vCORE
$2.52
Per Hour
Offerings
Pricing Offerings
Google Cloud SQL
IBM Cloud Databases
Azure SQL Database
Free Trial
Yes
No
No
Free/Freemium Version
No
No
No
Premium Consulting/Integration Services
No
No
No
Entry-level Setup Fee
No setup fee
No setup fee
No setup fee
Additional Details
Pricing varies with editions, engine, and settings, including how much storage, memory, and CPU you provision. Cloud SQL offers per-second billing.
When comparing cost, Google Cloud SQL typically offers a more straightforward and versatile plan than Azure SQL Database. Cloud SQL for PostgreSQL is a serverless solution provided by Google Cloud SQL that automatically modifies resources according to workload. For customers …
As I used Google Cloud SQL it's performance is very good and it's ui ux is as per the user demand. Apart from it the backend is very strong which makes it more usable tools as it gives or run the query in very minimal time. Yes there has to be some work on security and …
Google SQL was great as a first SQL provision. It quickly enabled the apps to be built and scaled as needed for a while. It was robust and adaptable as needed and easy to export as needed when ready, depending on growth. Cost-wise, it's a good choice and requires little …
The Google Cloud SQL offering fits into our development stack and was a clean replacement for our MySQL database. If we had been using SQL Server instead, then the offering from Azure would have made more sense. I have used both in the past and both work well, with GCP being …
At first, we choose Google Cloud SQL only for demo purposes. It is so easy to set up and It is fully managed. we have worked with Azure SQL as well but Google SQL is more simple to use and It fully secure, reliable, provides high availability, and very Low Latency.
Easier learning, simple features and settings with a very user-friendly application environment and flexible prices make Google Cloud [SQL] a pioneering option over competitors
Google Cloud SQL is just as good as the other guys. We were already invested in GCP, which made the choice very easy. We did not want to start fresh in AWS or Azure. We used our existing GCP setup and just added Cloud SQL. It's unfortunate that companies continue to send people …
There are many options for cloud-hosted dedicated SQL instances. In many ways, simply moving from software and server-based database to a dedicated cloud database is just generally good. All hosts provide some sort of scaling and backup, and all separate the server management …
Depending on the use case they stack up very well. Google and AWS are well suited multi-cloud strategies or those that need a high level of RDS performance.
It is very easy to setup SQL database on Azure. one can always refer to their documentation for best practices. It is highly available and scalable. It is cheaper than its alternatives and provide better performance than others. As we are using many other services of Azure for …
Does what it promises well, for instance, as a sidecar for the main enterprise data warehouse. However, I would not recommend using it as the main data warehouse, particularly due to the heavy business logic, as other dedicated tools are more suitable for ensuring scalable operations in terms of change management and multi-developer adjustments.
Less Appropriate Scenario: 1) Small Scale or Low Budget Projects 2) Organizations with limited expertise in cloud technologies may find the learning curve steep, especially if they are not familiar with the IBM Cloud platform 3) If database requirements are highly dynamic and change frequently, the comprehensive features and management provided by IBM Cloud Databases might be overkill. A more flexible, self-managed solution could be preferable for adapting to rapid changes.
We have found it's a great alternative for making older legacy applications work with online databases instead of only on-premises databases. We've converted over a dozen applications this way, and it has allowed our clients to have a distributed workforce using their applications without incurring the expense of a complete application rewrite.
The ease of setup was effortless. For anyone with development experience, a few simple questions such as name and login data will get you set up.
The web application to manage cluster settings, billing settings and even introspect the data was simple and most importantly worked all the time. This can not always be said for web interfaces of other products.
Maintenance is always an issue, so using a cloud solution saves a lot of trouble.
On premise solutions always suffer from fragmented implementations here and there, where several "dba's" keep track of security and maintenance. With a cloud database it's much easier to keep a central overview.
Security options in SQL database are next level... data masking, hiding sensitive data where always neglected on premise, whereas you'll get this automatically in the cloud.
Better cost reports, before just increasing to another tier, thus increasing the price. This is critical for early stage startups, where budget is tight.
Add more data center options. As a comparison, a similar service, Aiven.io has dozen more options than Compose (basically all big cloud providers). We moved from AWS to Digital Ocean, which made us stop using Compose, since Compose forces us to be either on IBM or AWS.
One needs to be aware that some T-SQL features are simply not available.
The programmatic access to server, trace flags, hardware from within Azure SQL Database is taken away (for a good reason).
No SQL Agent so your jobs need to be orchestrated differently.
The maximum concurrent logins maybe an unexpected problem.
Sudden disconnects.
The developers and admin must study the capacity and tier usage limits https://docs.microsoft.com/en-us/azure/azure-subscription-service-limits otherwise some errors or even transaction aborts never seen before can occur.
Only one Latin Collation choice.
There is no way to debug T-SQL ( a big drawback in my point of view).
IBM is our trusted partner which never failed to meet our expectations. Stability, efficiency, usability and security is a must have for our business which is fully provided by IBM Cloud Databases
As with other cloud tools, users must learn a new terminology to navigate the various tools and configurations, and understand Google Cloud's configuration structure to perform even the most basic operations. So the learning curve is quite steep, but after a few months, it gets easier to maintain.
IBM Cloud Databases' pricing structure is easy to understand, and if you choose the right product, you can operate your system at minimal cost. Although there is ample documentation available, there doesn't seem to be a user community running on it, so specific usage know-how and troubleshooting can sometimes take longer than expected.
The interfaces are intuitive once you are familiar with all the functions. The ability to use different tools to interact with the platform, such as directly via a browser or code editors such as VS Code or Visual Studio is a great option and allows for integrating withn the project and other testing and developing tools.
GCP support in general requires a support agreement. For small organizations like us, this is not affordable or reasonable. It would help if Google had a support mechanism for smaller organizations. It was a steep learning curve for us because this was our first entry into the cloud database world. Better documentation also would have helped.
Support is helpful enough, but we haven't always had questions answered in a satisfactory manner. At one time we realized that Compose had stopped taking database snapshots on its two-per-day schedule, and had in fact not taken one for many days. Support recognized the problem and it was fixed, but the lack of proactive checks and the inability to share exactly what happened has caused us to look elsewhere for production work loads
We give the support a high rating simply because every time we've had issues or questions, representatives were in contact with us quickly. Without fail, our issues/questions were handled in a timely matter. That kind of response is integral when client data integrity and availability is in question. There is also a wealth of documentation for resolving issues on your own.
Unlike other products, Google Cloud SQL has very flexible features that allow it to be selected for a free trial account so that the product can be analyzed and tested before purchasing it. Integration capabilities with most of the web services tools are easier regarding Google Cloud SQL with its nature and support.
The reason why I choose IBM Cloud Databases is that the IBM cloud toolset is already being used in other functions of the company and by using IBM Cloud Databases, the other cloud tools are better embedded and integrated. If the company is set to use amazon tools, I would go for rds.
We moved away from Oracle and NoSQL because we had been so reliant on them for the last 25 years, the pricing was too much and we were looking for a way to cut the cord. Snowflake is just too up in the air, feels like it is soon to be just another line item to add to your Azure subscription. Azure was just priced right, easy to migrate to and plenty of resources to hire to support/maintain it. Very easy to learn, too.
Improved integration with Google Cloud, we have set up some automations with Google Workspace, and we have noticed that the raw data sharing between them is very fast as compared to using some other managed database, not sure why.
Due to some downtime during maintenance, we had to set up a relatively small service which ingested the data while this went down and dumped it when it came back up. So this was a negative impact on our ROI, since now we had to remedy this downtime against the same profit margins
It was cheaper than the legacy aws service since we needed large database instances
