Google Cloud SQL Reviews

As a product manager and managed service provider for the solution, I help build AI using Google Cloud SQL, focusing mainly on Compute Machine. My organization uses Google SQL to host our app because the main package service is on cloud servers.

It is not the cool features that I find valuable, it is the stability of Google Cloud Platform, which is why we chose the platform over hosting our own servers.

It is hard to do logging with the solution. It is difficult to take out the exact log from the servers.

I have been using Google SQL for about three years.

I rate the stability an eight out of ten since we still have to check on the storage.

We are hosting around 10,000 end users on our app.

According to our engineer, the initial setup was okay. We have ten engineers on our team who worked on deployment.

We need a maximum of two back-end engineers to maintain the solution.

The solution is affordable. I rate it a six out of ten. We have a monthly license.

I cannot say Google Cloud SQL is good or bad because they have a good ecosystem. Google Cloud SQL is a good choice if you are using other Google services, but it is okay not to use the solution if you are not using the Google Cloud Compute Engine.

It is good to use compared to other services, so we are sticking with it.

Our primary use case is for lift and shift migrations. For example, from on-prem MySQL to the cloud.

It supports different databases, like Postgres and MySQL. It allows you even to migrate data from one DB to another one, for example, from MySQL to Postgres, et cetera.

The solution is stable and reliable. 

It's a scalable product.

The solution has been issue-free.

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.

We've only used the solution for four or five months. It hasn't been that long just yet. It's been much less than a year. 

It's quite stable. It's reliable. There are no bugs or glitches and it doesn't crash or freeze. The performance is good. 

We can easily scale the product as needed. It's not a problem.

We have eight to ten users at this time. 

We don't have any plans to scale at this time, however, it may be something we consider in the future. 

We've had no issues so far. We have not required technical support.

We previously used Postgres. Managing the DBs was a little tedious, so we migrated them to Cloud SQL.

There is no setup process per se. It's on the cloud and therefore there is nothing to upload or download.

We do have a technical team involved in the product, however, we don't have to worry about deployment or maintenance tasks. 

We have not needed any outside assistance. 

The is no license required. 

As a cloud product, we're always on the latest version of the solution. it self-updates. 

I'd recommend the solution. It is well suited for this lift and shift migration, especially if you are accessing everything within your VM. They have a Cloud SQL proxy and those things. It's easier to maintain and you don't really have to worry about the operation side of it.

I'd rate the solution eight out of ten.

Our primary use case of this solution is to have it run as a database for an application and to store data. We are using the public deployment model of this solution. It runs really well, it's cheap, it's efficient, it's user-friendly,

The most valuable features are that it's easy to use, simple, and user-friendly. 

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.

It's very stable, we haven't had any issues at all. 

It does have good scalability. We haven't had any problems with that. 

We have ten users using this solution. Those users are clients who we provide services for. We do have plans to increase usage.

In terms of how many staff are required for the maintenance of this solution, in our team, we are eight. We do many things. Our focus now is on BigQuery, so data warehousing. 

I have previously worked with Microsoft and Amazon AWS. I switched because I just like Google. I think it's a great platform. 

The two main competitors are Microsoft and Amazon Web Services. Out of these three, Google is the smallest when it comes to cloud in general, but I am pretty happy with how things are moving. I've been using Google for many years now and the services and it runs very well. I also use G Suite, Google Docs, you name it. It all works really well. It's user-friendly, to the point, it's not complicated. Whereas with Microsoft and some Amazon services can get quite complicated.

Although, maybe some of their services are more expanded, and maybe you can do some more. From a technical point, they are more advanced sometimes. You could say that for Amazon. My experience is that if a tool is easy to use and you get the job done in the fastest way possible, that tool has a great chance of becoming the leader because it's about user-friendliness. With Google, you get the job done and that's why you use these companies. 

The initial setup was straightforward. It took around ten minutes. 

I deployed this solution myself. 

We have seen an ROI from this solution.

It's really cheap. It wouldn't be more than, I believe it's around 50 euro per month for running a cloud SQL. 

There aren't any additional costs that I'm aware of.

I used Microsoft and Amazon and I also looked at Oracle, which is also an extraordinary company. When it comes to databases Oracle is very good. The problem with Oracle is that they're a bit of a world of their own. Whereas with Google, they're pretty open-source and open-minded, so they embrace the multi-cloud and hybrid cloud. That's what makes Google attractive.

Go for this solution because it gets the job done and it's cheap. You're up and running fast. That's what you want.

I would rate this solution a nine out of ten. Not a perfect ten because nothing is perfect.

We use the solution due to the fact that our server instance, the data center instance, is in GCP.

The speed is very good. 

It's useful in terms of the simplicity of doing backups. 

You can have redundant databases for reports, for posts, for example. 

It's SQL. SQL is so easy if you know something about databases. It's easy to learn. 

I like the cloud aspect.

The pricing of the solution seems reasonable. 

The solution is stable. 

Google seems to be working on a data lake solution, and we are happy with that.

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've been using the solution for two to three years.

The product is stable, however, maybe they need support for more databases. I remember some problems with the PostgreSQL integration with BigQuery or something like that. I don't remember now, however, from what I recall, we needed more support for other databases in GCP SQL.

We have maybe 200 people using the solution right now in our organization.

We also use PostgreSQL in GCP and BigQuery too for extract information from Jira.

The licensing is charged yearly, however, I don't manage the cost of the cloud in my company. I only work with Atlassian products. We are users of GCP for our instance. When I work with data in Google Cloud, our data people say the cost is not a problem. I can make a dump of databases daily and store extractions in buckets, for example, every day, full data, all days. And it's not a problem, cost-wise.

We are a customer and an end-user.

I'd rate the solution an eight out of ten.

We are focusing on data pipeline creation and data migration. It involves continuous streaming of data from one place to Google Cloud to be analyzed immediately.

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 have been using this solution for two years. 

This is a stable solution and offers good performance. 

As this product is cloud based, it is scalable. 

The technical support is good.

Positive

The initial setup is not that complex. 

From a financial perspective, Google Cloud SQL is on the cheaper side.

We did compare it with other solutions from Amazon and Microsoft. We received a special incentive from Google. That's why we went for Google Cloud SQL. 

I would rate this solution an eight out of ten. 

I am using it for database purposes. I am learning it to prepare for my certification. I have done a few big uploads, which I have removed later on.

I found its storage and security to be the most valuable. It was a good experience.

It is also very stable and scalable, and its support is perfect.

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.

I have started to use it very recently. It has been three-plus months.

Based on my experience so far, it has been very stable.

It is very scalable. We can add and remove the nodes and other things. We can also add servers and other patches as per the requirement.

We have a team of seven people who are using it currently. We are preparing for our certifications. Very soon, we will get some projects in our company, and at that time, we will use it officially.

They are perfect. I would rate them a 100 out of 100. Whenever I have faced an issue, I got full support from their side, irrespective of whether it was a small or big issue. They're really good people, and they helped me a lot. Their support is wonderful.

It was easy to set up.

I would recommend this solution. It has a lot of good features. It is easily scalable.

I would rate Google Cloud SQL a ten out of ten.

I primarily use it for marketing data and marketing analytics.

This version of Cloud SQL becomes a part of our larger data warehouse, which is just a part that the SQL manages. I work on the visualization part. So I usually already have all my data coming into my dashboard and that's where I get my insights from. I don't dig it out from the SQL.

Its most valuable feature is that it's scalable. I can start off with a base of a lot of data and move as much as I want and it's the same as if asked to do a lot of infrastructure changes. I can start a release model experiment on a thousand people, and if that experiment is a success I can run it on a million people, and the whole analysis doesn't require any changes so it's scalable that way. It's much more cost-sensitive. It's not that costly for me to do it.

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.

I have been using Google Cloud SQL for the last two months.

In terms of stability, Google Cloud SQL is very stable. There are stability issues but they get fixed when I'm running it for the smaller experiments or the smallest subset. So whatever code outlier situations exist, we are able to understand that it's a smaller subset and when we scale it back it is not really an issue.

As I mentioned above in the features section, Google Cloud SQL's scalability is one of its best features.

We get very good support from Google. If we have any questions at all we talk to them and they work it out. So it's very good.

I previously used a different solution for our marketing database, but it was very limited in scope. Moving forward, Google Cloud SQL is the only data warehouse I will ever use.

The initial setup was straightforward. Our deployment took around two months.

We implemented it ourselves. We are a consultancy company, so I asked my engineer to build it for us.

The advice I would give before starting up is to have a small interactive introductory session with some domain experts because even though it looks quite similar to MySQL and all the other SQL solutions out there, Google Cloud SQL lets me do a lot more. And it offers a lot of perks if you know how exactly to handle the product. So even if it is with a small, introductory session of two hours or three hours long, where the experts tell me that, "Hey, this is the whole scope of this solution or the product but it will be scaled up," it will help the end-users a lot because the documentation itself is not that extensive.

We have 11 - 12 people working with it - all marketing people.

On a scale from 1 to 10, 1 is the lowest and 10 the highest, I'd give it an 8.

We use Cloud SQL primarily as a database service and implement it in various systems, such as web systems.

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.

I have been working with Google Cloud SQL for about four or five years.

The stability is good overall, but some updates can affect service stability.

The product is scalable. It is more suitable for enterprise companies with specific needs and restrictions.

The customer service and support are good, but the service could be improved for enterprise users who require very short response times.

Neutral

The initial setup process is generally not very complex, although some exceptions can complicate it.

The platform integration with other Google products provides a connected solution. While I recommend Google Cloud SQL, the product choice depends on the specific use case. 

I would rate Google Cloud SQL as an eight.