Google Cloud SQL Reviews

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. 

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.

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.

The primary use case for this solution is real-time communication software, chatting services and a few other different services running on the mobile apps. So, the primary requirement for Google SQL was taking off the management heading.

It's all built into the web browser, so any operating system will work. It's easy to manage. They help me take care of the replication data backups and software upgrades, updates and so on. They take care of everything.

I no longer need experts in database management. When I say database management, I don't mean SQL commands and which command is better or which query is better constructed. The database management in terms of memory, configuration, disc space, archiving, back-ups, replication problems, updates and so on. So, I no longer need someone or a team of people sitting around, taking care of my database infrastructure. I only have Google for that.

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.

Quite honestly my usage so far did not test the limits of scalability. I cannot really comment on that one.

I have not used technical support. 

When we were using the Rackspace, we only used Rackspace virtual machines, for our virtual machine requirements, as well as our own SQL requirements. So, we had virtual machines, hosting SQL databases. And, it didn't really work out in our favor.

It was very straightforward. Just a couple of clicks, and we were done.

The pricing is very much an important factor as to why we use this solution.

When considering other options, we considered AWS, Google Cloud, Ocean and Rackspace UK.

I need to make sure that my data is stored securely, transported securely and accessed securely. And the second thing is the number of options I have. Google Cloud SQL gives us more options. 

My suggestion to anyone thinking about this solution is to jump into it head-first!

We work with the solution for various databases because it's easier to use, integrate with, maintain, and simplify backup.

The valuable feature of Google Cloud SQL is its high availability option, allowing for the selection of two backups and two databases. This ensures minimal downtime, adhering to SLAs that guarantee the database will not be down for over a few seconds.

The customer support should be improved.

I have been using the solution for the past three years.

The product is stable.

The support team responds quickly. However, it takes a long time to fix the issue or to help you with the solution.

The initial setup was straightforward.

It is not expensive, especially considering the significant reduction in database management time.

I recommend to experience the value of the solution.

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.

• Automated backups
• Read replicas
• Integration with other GCP services

Reduced management overhead on the DB side; scripted env-ts (setup and tear down of the infrastructure within GCP).

• Accessibility over internal network, rather than by public IP only
• MySQL clustering (rather than replication or failover only)

Not really, as long as GCP infrastructure is up.

For write operations – yes, as there is no MySQL clustering mode.

Hosted MySQL DB, maintained by DBA; reason for switch: overall move to the cloud of other GCP components.

Very straightforward, just a simple page to configure DB capacity and some additional attributes.

Licensing is not applicable; pricing is reasonable. Slightly more expensive than corresponding Google Compute Engine instance.

Most benefit would be for organizations which are moving other services to Google Cloud.