I use Google Cloud Spanner in my company as a relational database. In general, my company uses Google Cloud Spanner for anything that needs a relational database behind the scenes or in the company.
Google Cloud Spanner is a fully managed, scalable, globally distributed, and strongly consistent database service. It offers traditional relational database semantics alongside non-traditional scale and availability.


| Product | Mindshare (%) |
|---|---|
| Google Cloud Spanner | 7.5% |
| MongoDB Atlas | 11.9% |
| Amazon RDS | 11.8% |
| Other | 68.8% |
Google Cloud Spanner is designed for applications that require high availability, strong consistency, and the ability to scale across regions without sacrificing performance. It supports SQL semantics and guarantees ACID transactions. With seamless horizontal scaling, it enables businesses to automatically expand their databases in response to load demands, maintaining performance and reliability. Built with advanced technology, it provides developers the ability to focus on building applications without worrying about infrastructure complexity.
What are the key features of Google Cloud Spanner?Google Cloud Spanner's implementation in the finance sector facilitates real-time transaction processing and fraud detection systems. In retail, it handles large volumes of transactional data, supporting services like inventory management. Healthcare uses it for managing patient data across geographic locations, ensuring data consistency and accessibility.
Google Cloud Spanner was previously known as Google Spanner.
Streak, Optiva, Mixpanel
| Author info | Rating | Review Summary |
|---|---|---|
| Infrastructuer Security at Premise Data | 4.5 | I use Google Cloud Spanner primarily for its scalability, enabling horizontal scaling without downtime. However, the developer experience is hindered by the lack of a functional local emulator, and features like geolocation queries and full-text search are missing. Despite this, I've seen a positive ROI. |
| System Architect at UST Global España | 5.0 | I use Google Cloud Spanner alongside Cloud SQL for integration due to its advantages similar to Cloud SQL storage. However, it lacks AI features. I'd like AI capabilities similar to those offered by other platforms, like Microsoft’s low-code tools. |
| Data Engineering and AI Intern at .3Lines Venture Capital | 4.5 | I found Google Cloud Spanner to be useful but needing improvement in horizontal scaling. While there were no alternate solutions considered, I didn't see an immediate return on investment and utilized no specific cloud provider for deployment. |
| Senior Technical Architect at HCL Technologies | 4.0 | I use this solution for multi-regional data, valuing its scalability and stability as a managed service, which outperforms RDBMS. Despite the high cost, I recommend it and rate it 8/10. |
| Digital Marketing Manager at BEXCOM - Tech | 5.0 | I find the application deployment in Google Cloud Spanner to be its best feature. However, I would like to see improvements in the deployment of cameras and surveillance infrastructure, specifically the integration of AI for enhanced video monitoring. |

I use Google Cloud Spanner in my company as a relational database. In general, my company uses Google Cloud Spanner for anything that needs a relational database behind the scenes or in the company.
With Google Cloud Spanner, the total cost of ownership or TCO is great. The tool doesn't have a lot of DevOps overhead costs related to maintenance, setup phase, and usage. With another relational database that runs on the cloud, you have to do a lot of extra stuff just to be able to connect your runtime to the database or just to run a simple query against the database. With Google Cloud Spanner, you have a web interface that is provided to you. Authentication is added and made a part of Google Cloud's IAM capability. You don't have to figure out how to securely connect to the database since you just use Google Cloud's IAM. On the scalability side, Google Cloud Spanner is the only relational database that can be distributed horizontally worldwide. With Google Cloud Spanner, you get infinite scaling options for a relational database.
The most valuable feature of the solution is its scalability. Scalability comes with two options, among which Google Cloud Spanner can scale horizontally, compared to other relational databases that scale vertically. You can change Google Cloud Spanner's resource configuration, which is done through processing units. Suppose you set up Google Cloud Spanner initially with a hundred processing units, and then you run out of resources since your database used too much CPU. In the aforementioned scenario, you can scale up or down and face no downtime in the production phase. The solution's features are important when running a company twenty-four hours, seven days a week.
Considering the developer experience, it is very hard to run Google Cloud Spanner locally. Google came up with something called Cloud Spanner Emulator, which fails to work like the real product if I want to develop some code and run a database locally on my machine. The aforementioned area of the solution can be considered for improvement.
Postgresql databases support geolocation queries, and I would like to see something similar in Google Cloud Spanner. Something equivalent to Full Text Search from Postgres is another feature I would like to see in Google Cloud Spanner.
I have been using Google Cloud Spanner for three years. It is a managed service, so my company doesn't really have control over the product's version.
It is a stable solution. I never had issues with the solution's stability. Stability-wise, I rate the solution a ten out of ten.
Scalability-wise, I rate the solution a ten out of ten.
I rate the technical support a seven out of ten.
Neutral
The initial setup of Google Cloud Spanner requires just two clicks from the user.
I have seen a return on investment from the use of Google Cloud Spanner in my company.
The deployment phase did not cost my company anything, but the runtime of the solution is an expensive area.
Google Cloud Spanner is an expensive solution. The solution does lower our costs related to the database, which alone is expensive since our engineers don't need to invest in doing a lot of troubleshooting or trying to figure out how to connect this solution, making the total cost of ownership to be on the lower side of the spectrum.
Though Google Cloud Spanner is a relational database, there are some things that a person needs to know upfront. If your database schema is way too Static, you know how it will look if you use Google Cloud Spanner. If you make a lot of changes in the database schema during the development life cycle, you shouldn't consider the use of Google Cloud Spanner initially. A schema change is a pretty complicated process in Google Cloud Spanner.
I rate the overall solution a nine out of ten.
Google Bigtable and Google Cloud Spanner are the same. We can forward all the Cloud SQLs on Google Cloud Spanner, which is used for integration purposes. We use Cloud SQL with Google Cloud Spanner. If you have support for Cloud SQL, the same can be used for Google Cloud Spanner. I believe the storage will be in the Firestore or Datastore.
The product's advantages revolve around its similarity to Cloud SQL storage. The same can be said about Low-Code Microsoft SQL Server. The same set of advantages is available in Microsoft and Google Cloud Spanner. The advantages are associated with the product because they were also early available in the tool, and they are all the same to this day.
The tool lacks to offer AI features. In the future, I would like the product to offer AI features to users.
Nowadays, we are creating small acronyms for our SQL Server. We put some templates. If I just put your name and stop it, the entire cloud can be explored, but such features are not there in Google Cloud Spanner. As a layman rather than a developer, if I create a tool or a procedure. If I write a procedure and then when you describe a procedure, a dummy procedure will be written for you, and it will be available for you as a template in SQL Server, but such kind features are not there in Google Cloud Spanner.
I have been using Google Cloud Spanner for three to four years.
It is a very scalable solution. You can increase the number of node as much as you want. It depends upon the region where you stay.
The support is excellent with Google.
You need to know how to deploy it. You need to have the GCP certification. Once you have a GCP certification, then it won't take much time to deploy the application. Unless you have a deployed GCP-certified employee, you will need to study GCP very well. There is a lot of focus needed to study Google and its cloud functions are there, the App Engine Application Platform is there, and then there are Kubernetes, which is for containers. You put all your applications in Kubernetes. You need to study Google Cloud Spanner to be able to maintain the data and everything. If you know everything, then Google Cloud is better compared to Azure. I have been using Google Cloud for a very long time; I prefer Google Cloud for everyone over Azure.
Only one person is required to deploy the product.
If you know how to deploy the product, then maximum within a day, you finish the deployment process. If the configurations and everything are done, it won't take much time. You just deploy the application. The time required to deploy the product also depends on the region where the tool will be used. Suppose we are doing employment in the Asia Pacific region. In that case, the tool should only be accessed in that region, but if you are going to access the same in North America and all, you need to know how to deploy the tool as per the timings in the North American region while also taking care of GCP. If your application is running only in Asia, you can deploy the application in the Mumbai region, which is in the Asia Pacific region. When you see the same application running in Northern America, you need to consider the same for the Northern America region in the GCP cloud, and such a consideration is something you should have before you start with the deployment.
Price-wise, I heard that Google Cloud Spanner is on the higher side. I am not sure if this is a rumor or if it's fake news, but I believe that having BigQuery and GCP together could be a little costly compared to other tools like Azure. In the product, if I look at the advantages, I can see that the tool has speech recognition, translation, machine learning, and everything else is accessible in GCP. I am using Google Cloud, and I know which features are already there in the tool. When you are using all the tools, you need to pay for them.
Performance-wise, the tool is working fine. With the tool, the trigger is not there. That is one of the things I noticed, as we cannot see or create a trigger. It is not possible to create a trigger, update a trigger, or delete a trigger. There could be some alternative in Google Cloud Spanner to create the trigger and all. Definitely, there must be some solution and I am very eager to explore such areas.
If you ask me, I would say that I can easily maintain the product because I know about it if somebody is not aware of how to configure or how to do App Engine's configuration in Google Cloud, where App Engine and Kubernetes are core parts of the application. If you know App Engine and Kubernetes, then you can maintain it easily. Google Stackdriver allows you to trace all your configurations.
There are a lot of features in Google products. Firstly, try to explore all the features before start to use the tool since then only you can use it. All the features are available in the tool and one should not doubt over why one can't utilize them.
I rate the tool a nine out of ten.

The tool needs to improve horizontal scaling.
I have been using the product for a year.
Google Cloud Spanner is stable.
My company has 15-20 users for the product.
The tool's deployment is easy.
The solution is expensive.
You need to look at the data set and company requirements. I rate the product a nine out of ten.

We use the solution for mainly multi-regional relational data where you need to scale well and RDBMS does not. We chose the solution for scalability and multi-regional use cases.
It spans well. Normally, we have issues with MySQL and other relational databases, however, this is not an issue with Spanner.
The service is managed.
The solution is stable and reliable.
We can scale the solution if we need to.
We haven't had problems with the product at all.
The cost can be a bit high.
I've been using the solution for four or five months actually.
It's a very stable service. We haven't had any issues with it. There are no bugs or glitches and it doesn't crash and freeze.
It is very scalable. It's not a problem to expand.
We only have seven or eight people using the solution right now. It's not used too widely just yet.
We do not have plans to increase usage right now.
We haven't had any issues with the product and therefore have not reached out to support for any reason. I can't say how helpful or responsive they would be.
We've used MySQL, PostgreSQL, and other services.
There is no installation required. It's a managed service.
There's no license required, as it is a managed service.
The solution is expensive.
We're using the latest version of the solution as it's a cloud product. It always self-updates.
I'd recommend the solution to other users.
From what I have experienced so far, I would rate it eight out of ten. I've been happy with its general capabilities.
I am currently working as an independent consultant and am not part of a company that uses Google Cloud Spanner.
My ultimate goal is to work on the deployment of Google Cloud Spanner in other infrastructure projects as well.
The application deployment in the cloud is the best feature of the infrastructure.
A feature I want to improve is the deployment of cameras and surveillance infrastructure.
The current functionality is important, but artificial intelligence for camera and video surveillance would be a valuable addition to the infrastructure.
I have been using it for one year.
It is a stable product.
It is a scalable product.
The tech support team is very supportive.
Positive
The initial setup is very easy.
It is expensive.
Spanner is a very good infrastructure offered by Google Cloud, but I personally lack experience in Python since I only received my diploma in January. Spanner is easy to use for those with experience in Python and machine learning, and that deployment and execution are currently working well.
I would rate it a ten out of ten.