Co-Founder at a tech services company with 11-50 employees
Real User
Top 5
Nov 6, 2025
Sometimes the sharing with third parties or configuring that in Google Cloud SQL is not the most intuitive. From a user perspective, if Google Cloud SQL integrated AI directly into the query so that I could type something much quicker and then it would sort out exactly the query, that could help.
Google Cloud SQL needs to improve its support for high-end I/O operations. On-prem systems with high I/O capabilities perform better, as Google Cloud SQL takes more time to handle the same tasks. There is also difficulty in changing the time zone after the database is set up. Moreover, some features available in MSSQL on-prem are missing on Google Cloud SQL, affecting migration potential.
I would appreciate more flexibility with specific extensions applicable to engines like PostgreSQL. This would enhance the capabilities of Google Cloud SQL.
The overall documentation and the connectors need improvement. The performance compared to AWS is not as fast, and the technical support could be better as they don't have a dedicated team, but mostly AI handles the support now.
When discussing media files, such as images and audio files, stored in Google Cloud, concerns about handling large amounts of data arise. If these files exceed 3 GB, backing them up can be challenging. The scalability of managing large media files can be tough. For example, recording a voice clip increases storage requirements fluidly. Therefore, solutions to reduce the volume of audio or video files should be considered.
IT architect at a tech services company with 5,001-10,000 employees
Consultant
Top 20
May 27, 2024
The product's user interface could be more user-friendly to improve the overall user experience. In some situations, on-premises solutions offer more flexibility, so further investigation into these areas would be beneficial.
The most challenging part is dealing with legacy data from your old systems and migrating it into the new setup, but once you've completed the data migration, it becomes quite convenient to use.
We have not had any major issues with the solution. The only thing that could be better is the pricing. The best features of the solution are too expensive for our company's budget. Additionally, adding AI integration to Google Cloud SQL would be valuable, especially for security like fraud detection and monitoring login activities in the database. These features could boost data security.
The purging of the data could be better. We don't have a good mechanism to deal with the old data, especially when the data grows. We see latency issues, so we were forced to introduce an in-memory store. Otherwise, the solution is fine. The enterprise edition is quite expensive.
Chief Architect at a energy/utilities company with 10,001+ employees
Real User
Top 10
Jul 7, 2022
Knowledge graphs and data integration is very important for distribution for our business. To create a seamless data integration, the title integration of these databases with the data integration platforms is essential. This is what we would like to have in a future release. We would also like to have artificial intelligence capabilities. We are exploring the leverage of Machine Learning Algorithms for workload prediction and AI capabilities would assist in this regard.
We haven't had any issues and have not come across missing features. The monitoring part could be better. People who are not very, very technical and who may be more on the business side, find that it can be a little difficult to understand the metrics. That probably can be simplified.
Other clouds, like Azure, have some specific products, and Google doesn't have something like that. For example, if you work in Google, you can use Dialogflow to make a chatbot. However, the Azure methodology or system is more powerful for those chatbots. In the case of Google, they need to work on a more easy interface for users. Azure is easier to learn. I don't know why. I like the Azure system, even though I'm a user of Google. I don't like it when on the screen you can't follow the steps clearly. The user interface just isn't as intuitive. When it comes to Google Cloud, in order to do something, you need to read more maybe. It requires more research and learning.
Senior Consultant at a computer software company with 10,001+ employees
Vendor
Feb 9, 2021
I am yet to explore a lot of features that are present in this solution. However, it would be good if more documentation is available for this solution. This would help us in preparing for the certification exam and understand it better. Currently, we don't have much documentation. We do the labs for 20 or 25 minutes, but we can't capture and download anything.
Commercial and Operations Director at SygmaTel, BlaBla Connect, KnowMe Solutions
Real User
Dec 23, 2019
In my humble opinion, nothing can be improved. It's a good solution as it is. What could be refined however is the ability to have more than just one secondary/replication site. At the moment you can have a primary DB and a replica one, but having the option to add a third or fourth replication site would be fantastic.
The only room for improvement here is that they need to connect to more existing data sources so that it becomes easier for a layman to get a more realistic understanding of what's happening. They don't put data outside of the cloud storage. If I can query and there is some way for me to ingest it with various query cells, that would be great. Better connectivity with other marketing tools would be helpful. Right now it's limited in scope relative to the other connectors. So they should build more connectors, making it easier to connect the data. There's no standalone application that I could just click and start shooting it.
Better integration with other tools could improve this solution. For example, data analytics is very important, so that's why I go to BigQuery. They should make things more user-friendly, not technically on the use of SQL but when it comes to integrating it with other tools, it could be like dashboards or business intelligence. I believe Google is already working on that as well because they bought Looker about a month ago. I would like to see better integration with all the different tools on the platform.
Commercial and Operations Director at SygmaTel, BlaBla Connect, KnowMe Solutions
Real User
Sep 25, 2018
In my opinion the most vulnerable problem with Google SQL is each SQL node is provided with a public IP address. They provide you the option or ability to customize your access control list, but at the end of the day, it's a public IP address.
Google Cloud SQL is a fully-managed database service that makes it easy to set up, maintain, manage, and administer your relational PostgreSQL and MySQL databases in the cloud. Google Cloud SQL offers high performance, scalability, and convenience. Hosted on Google Cloud Platform, Cloud SQL provides a database infrastructure for applications running anywhere.
Sometimes the sharing with third parties or configuring that in Google Cloud SQL is not the most intuitive. From a user perspective, if Google Cloud SQL integrated AI directly into the query so that I could type something much quicker and then it would sort out exactly the query, that could help.
Google Cloud SQL needs to improve its support for high-end I/O operations. On-prem systems with high I/O capabilities perform better, as Google Cloud SQL takes more time to handle the same tasks. There is also difficulty in changing the time zone after the database is set up. Moreover, some features available in MSSQL on-prem are missing on Google Cloud SQL, affecting migration potential.
I would appreciate more flexibility with specific extensions applicable to engines like PostgreSQL. This would enhance the capabilities of Google Cloud SQL.
The overall documentation and the connectors need improvement. The performance compared to AWS is not as fast, and the technical support could be better as they don't have a dedicated team, but mostly AI handles the support now.
When discussing media files, such as images and audio files, stored in Google Cloud, concerns about handling large amounts of data arise. If these files exceed 3 GB, backing them up can be challenging. The scalability of managing large media files can be tough. For example, recording a voice clip increases storage requirements fluidly. Therefore, solutions to reduce the volume of audio or video files should be considered.
They could improve documentation and dashboard stability for efficient user experience and database management.
The product's user interface could be more user-friendly to improve the overall user experience. In some situations, on-premises solutions offer more flexibility, so further investigation into these areas would be beneficial.
The most challenging part is dealing with legacy data from your old systems and migrating it into the new setup, but once you've completed the data migration, it becomes quite convenient to use.
For data analysis, the AI area of the product has certain shortcomings where improvements are required.
The customer support should be improved.
We have not had any major issues with the solution. The only thing that could be better is the pricing. The best features of the solution are too expensive for our company's budget. Additionally, adding AI integration to Google Cloud SQL would be valuable, especially for security like fraud detection and monitoring login activities in the database. These features could boost data security.
It is hard to do logging with the solution. It is difficult to take out the exact log from the servers.
I would like to see better availability of the product in different regions. It should also improve the security with encryption.
The purging of the data could be better. We don't have a good mechanism to deal with the old data, especially when the data grows. We see latency issues, so we were forced to introduce an in-memory store. Otherwise, the solution is fine. The enterprise edition is quite expensive.
Knowledge graphs and data integration is very important for distribution for our business. To create a seamless data integration, the title integration of these databases with the data integration platforms is essential. This is what we would like to have in a future release. We would also like to have artificial intelligence capabilities. We are exploring the leverage of Machine Learning Algorithms for workload prediction and AI capabilities would assist in this regard.
We haven't had any issues and have not come across missing features. The monitoring part could be better. People who are not very, very technical and who may be more on the business side, find that it can be a little difficult to understand the metrics. That probably can be simplified.
Other clouds, like Azure, have some specific products, and Google doesn't have something like that. For example, if you work in Google, you can use Dialogflow to make a chatbot. However, the Azure methodology or system is more powerful for those chatbots. In the case of Google, they need to work on a more easy interface for users. Azure is easier to learn. I don't know why. I like the Azure system, even though I'm a user of Google. I don't like it when on the screen you can't follow the steps clearly. The user interface just isn't as intuitive. When it comes to Google Cloud, in order to do something, you need to read more maybe. It requires more research and learning.
I am yet to explore a lot of features that are present in this solution. However, it would be good if more documentation is available for this solution. This would help us in preparing for the certification exam and understand it better. Currently, we don't have much documentation. We do the labs for 20 or 25 minutes, but we can't capture and download anything.
In my humble opinion, nothing can be improved. It's a good solution as it is. What could be refined however is the ability to have more than just one secondary/replication site. At the moment you can have a primary DB and a replica one, but having the option to add a third or fourth replication site would be fantastic.
The only room for improvement here is that they need to connect to more existing data sources so that it becomes easier for a layman to get a more realistic understanding of what's happening. They don't put data outside of the cloud storage. If I can query and there is some way for me to ingest it with various query cells, that would be great. Better connectivity with other marketing tools would be helpful. Right now it's limited in scope relative to the other connectors. So they should build more connectors, making it easier to connect the data. There's no standalone application that I could just click and start shooting it.
Better integration with other tools could improve this solution. For example, data analytics is very important, so that's why I go to BigQuery. They should make things more user-friendly, not technically on the use of SQL but when it comes to integrating it with other tools, it could be like dashboards or business intelligence. I believe Google is already working on that as well because they bought Looker about a month ago. I would like to see better integration with all the different tools on the platform.
In my opinion the most vulnerable problem with Google SQL is each SQL node is provided with a public IP address. They provide you the option or ability to customize your access control list, but at the end of the day, it's a public IP address.