It's dramatically faster than running MySQL on a VM, which is what we did before. Whatever Google has done to optimize Google Cloud SQL compared to standalone MySQL installations has worked.
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 …
Given this is a hosted solution, database a service it helps in removing the effort of maintaining these databases manually. Eases out the pain of upgrading, applying security patches and keeping things running without having to worry about missed changes. The database can be …
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 …
Google Cloud SQL is very similar to other cloud provider options. AWS and DigitalOcean are direct competitors, While Azure is focusing on their own products. At cloud provider level, it's a matter of choosing the provider, and this product will not play a significant role on …
As I have been commenting in our company, we have solved our performance problems and responses obtaining speed in the queries occupies less disk space, in addition to its price and all the tools of great Scope it possesses.
It was quite challenging to choose between these as they both have their pros and cons. But as far as we were concerned the decision to adopt the MYSQL database for our production was because it is an open-source language. This makes it very compatible with our needs and was …
MongoDB has a dynamic schema for how data is stored in 'documents' whereas MySQL is more structured with tables, columns, and rows. MongoDB was built for high availability whereas MySQL can be a challenge when it comes to replication of the data and making everything redundant …
Having used both PostgreSQL and Microsoft SQL Server, I can tell that MySQL performs admirably in a Linux setting. When compared to Microsoft SQL Server, the extra benefit is the minimal or nonexistent licence fee. We find that MySQL's programming interface is particularly …
MySQL stands up and above the list of different softwares available online. I find it to be easy to use, scalable, and has good performance as compared to other softwares.
Better and more useful automation tools are available. Better at scaling and hosting your data. Greater security around access of data and encrypting where required. Allows for seamless integration in other Azure solutions which allows for greater flexibility when using the …
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.
MySQL is best suited for applications on platform like high-traffic content-driven websites, small-scale web apps, data warehouses which regards light analytical workloads. However its less suited for areas like enterprise data warehouse, OLAP cubes, large-scale reporting, applications requiring flexible or semi-structured data like event logging systems, product configurations, dynamic forms.
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.
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.
Learning curve: is big. Newbies will face problems in understanding the platform initially. However, with plenty of online resources, one can easily find solutions to problems and learn on the go.
Backup and restore: MySQL is not very seamless. Although the data is never ruptured or missed, the process involved is not very much user-friendly. Maybe, a new command-line interface for only the backup-restore functionality shall be set up again to make this very important step much easier to perform and maintain.
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).
For teaching Databases and SQL, I would definitely continue to use MySQL. It provides a good, solid foundation to learn about databases. Also to learn about the SQL language and how it works with the creation, insertion, deletion, updating, and manipulation of data, tables, and databases. This SQL language is a foundation and can be used to learn many other database related concepts.
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.
I give MySQL a 9/10 overall because I really like it but I feel like there are a lot of tech people who would hate it if I gave it a 10/10. I've never had any problems with it or reached any of its limitations but I know a few people who have so I can't give it a 10/10 based on those complaints.
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.
We have never contacted MySQL enterprise support team for any issues related to MySQL. This is because we have been using primarily the MySQL Server community edition and have been using the MySQL support forums for any questions and practical guidance that we needed before and during the technical implementations. Overall, the support community has been very helpful and allowed us to make the most out of the community edition.
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.
MongoDB has a dynamic schema for how data is stored in 'documents' whereas MySQL is more structured with tables, columns, and rows. MongoDB was built for high availability whereas MySQL can be a challenge when it comes to replication of the data and making everything redundant in the event of a DR or outage.
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