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 …
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.
Your upcoming app can be built faster on a fully managed SQL database and can be moved into Azure with a few to no application code changes. Flexible and responsive server less computing and Hyperscale storage can cope with your changing requirements and one of the main benefits is the reduction in costs, which is noticeable.
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.
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).
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.
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.
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.
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.
With managed database system, it has given us near 100% data availability
It has also improved web layer experience with faster processing and authentication using database fields
Google Cloud SQL also gels up well with Google Analytics and other analytics systems for us to join up different data points and process them for deeper dives and analysis