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.

The solution is easy to use. I am impressed with the tool's features and functionality. 

I would like to see better availability of the product in different regions. It should also improve the security with encryption. 

I have been using the product for six years. 

I would rate the product's stability an eight out of ten. 

I would rate the tool's scalability a seven out of ten. My company has more than 2000 users for the solution. 

The tech team's response is delayed. Also, it's difficult to get a resource. 

Neutral

I have used AWS and Azure before. 

The solution's deployment is easy but integrating it with some applications is a bit difficult. The tool's deployment took more than two hours to complete. 

I myself did the deployment. 

You need to pay extra costs for backup and replication. 

I would rate the solution a seven out of ten. You will need around 10 admins to maintain the tool. 

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.

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.

Our primary use case involves deploying the platform within a private VPC environment, where we heavily rely on its managed services for product deployment and ongoing data management tasks.

The product’s automatic scaling feature is particularly advantageous for accommodating large volumes of data. Additionally, the query insights provide valuable analytics for optimizing performance and identifying potential issues.

They could improve documentation and dashboard stability for efficient user experience and database management.

We have been using Google Cloud SQL for approximately two years.

I would rate the product a seven in terms of stability, with occasional minor issues that are promptly addressed by Google's technical support.

The platform is highly scalable. It offers robust features. Our clients primarily consist of enterprise businesses, as it caters to their complex infrastructure and security needs. 

I rate the scalability an eight.

The technical support team offers responsive assistance, although there is room for improvement in certain areas.

Neutral

The setup process was straightforward, involving simple configuration steps within the Google Cloud environment.

Our deployments are typically within a private VPC environment, and the duration depends on the scale and architecture of the project, ranging from a few days to weeks for larger implementations.

The return on investment is significant for us, as Google Cloud SQL is integral to our product offerings and data management infrastructure.

While the platform’s pricing may be higher, it aligns with industry standards, considering the quality of service and features provided.

Google Cloud SQL enhances our AI-driven projects by providing features like query optimization and scalability for efficiently processing large datasets. Additionally, recent updates, such as the optimization feature for Germany, further contribute to improving performance and supporting our AI initiatives.

Despite minor areas for improvement, it offers robust features and scalability that make it a valuable asset for businesses seeking efficient data management solutions.

Overall, I rate it an eight.

We use it for managing workflows, workflow data, and state management. We'll use it for tenant metadata information and keeping it. 

We have some BI use cases as well. We are in the automation industry, so, in general, whatever is required for automation, we keep all that information. 

We are using standard SQLs features only, so we don't use any very specific feature assets.

One feature we've found pretty interesting was their support, which is multi-region support. They have good multi-region failure support, and we can just set up there and read replicas directly and we can fall back. We are quite pleased with the results.

The initial setup is straightforward. 

It's stable. 

The solution can scale. 

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. 

I've used the solution for a few months. 

The stability is good. There are no bugs or glitches. It doesn't crash or freeze. 

Currently, our DevOps team is using the product, and we have 20 to 30 people using it. We have plans to increase usage. 

While it is scalable, I don't yet have practical experience with the process. 

The solution is very easy to set up. It's not overly complex. 

The deployment is very fast. It was only a few minutes.

I'd rate the solution three and a half out of five in terms of ease of setup.

I'd rate it higher if there was general serverless support or good best practices by way of documentation for setting everything up. We are using the enterprise model. Having best practices and serverless support would make it a bit better.

Right now, we don't need much maintenance as we're still in the beginning stages and don't have much production workload.

We were able to handle the setup ourselves. The documentation was good enough to follow so that the setup was easy.

The pricing is interesting. For the enterprise edition, it was almost three times the cost of the standard edition. There should be some more clarity on that. It was not very clear why it's so much more or what the differences are. It requires better documentation. 

We're a customer and end-user.

We moved quite recently in production. In terms of the development run, we were on AWS. Now, some of the workloads we are moving to GCP even though we have been an Amazon shop for a long time. 

We are working on the latest version of the solution. 

I'd rate the solution 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.

GCP hosts our entire infrastructure, both internally used systems, and externally-facing ones. Back to back this means that Google Cloud SQL is used for all SQL related requirements by our systems.

The main benefit to our organization is the fact that we no longer need DB admins that take care of the physical servers, backups etc... All this is managed by GCP.

In terms of most valuable features - its ease of management and the ability to oversee the statistics of your SQL, and obviously its availability all the time.

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.

We've been using it for around 2 years.

Google Cloud SQL is very stable.

It is highly scalable. You can quickly add the disc space and you can quickly add different discs and nodes.

Everyone in our company is using Google. Emails are Google. Everyone's using Google. All infrastructure for our operation is on Google. The more business we have the higher the usage.

Google's technical support is good, but they tend to never reopen a case and to send us snippets from the publicly available documentation. It's not as helpful as you would expect, not just for Google Cloud SQL but for all of Google Cloud products.

The initial setup was quite simple. It took maybe 10, 20 minutes

On a scale of 10, I'd give it a 10. 

I would recommend everyone to check all of Google's Cloud portfolio and give it a shot.

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.

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.