We are tracking because we have an integrated system. We have some integration with external third parties. We also track the data that we get from external sources. In Postgres, we can handle maybe ten million records per month. We use partitioning and healing features to manage this growth in data. Google Cloud SQL provides fast and very short transactions when modifying our data, using Postgres as our database system across multiple ports. It performs queries for data and handles purchases based on those queries. The scalability with Postgres is impressive. Currently, we are in a beta phase, utilizing three instances. There were issues with write and read instances. Also, there were delays in data synchronization between the write and read columns. When data is written to the write instance, it's not always immediately available in the read instance, causing a delay of up to 20 seconds. We have the right systems to manage the necessary operations. Sometimes, we have one instance for handling requests; at other times, we might have more than two instances. Querying the correct data is fast. However, read queries can be slower due to the large amount of data they need to process. We use additional processing power from more instances to accommodate the required scale. Google Cloud SQL is straightforward. The setup and configuration are easy, and managing the team is simple. We have one dedicated person per week to handle incidents or disturbances in the process and perform additional work. It's enough for maintenance and support. As data accumulates, it's crucial to devise a strategy for managing its volume, which involves using historical tables, archiving, or partitioning. These methods are all useful. As the data volume increases, query execution times can slow down. Therefore, it's imperative to implement an effective indexing strategy. By optimizing indexes, partitioning, and other techniques, queries can be executed more efficiently, even when querying on multiple parameters. There could be two or three read instances. The synchronization between the write and the read is very fast. There are multiple advantages to Google Cloud SQL. Firstly, it operates in the cloud, making it accessible from anywhere. Unlike competitors, Google Cloud SQL is fully integrated into the cloud environment. You can quickly scale your resources up or down according to your needs, growing or decreasing. This flexibility allows you to stay aligned with current demands while optimizing costs. Overall, I rate the solution a nine out of ten.
My organization uses AWS and not Google Cloud SQL for web applications. Instead of Google Cloud SQL, my company uses services from Amazon RDS and Treasure Data's DMP to support my company's data storage for analytics workloads. The features of Google Cloud SQL I find most beneficial for database management stems from the fact that all the employees in our company can access it. I don't know about the impact of the product's scalability in our organization since there is another section in my company that manages it. I don't take care of the maintenance part of the product. I also am not involved in the troubleshooting process related to the product since there is another team in my company that takes care of such areas. There are 20 engineers in my company who take care of the maintenance part of the product. The integration capability of the product with the services offered by Google is very good. The reliability offered by the product is enough for my company. I rate the overall tool a seven out of ten.
My advice to people who are considering using Google Cloud SQl is to consider your budget and performance needs when picking Google Cloud services. If you have a big budget and need high performance, go for Google Cloud SQL. But if you're a small company with budget constraints, use VM instances with databases inside to save money. Overall, I would rate the solution an eight out of ten.
Product Manager at a tech services company with 201-500 employees
Real User
Top 10
2023-06-22T08:02:00Z
Jun 22, 2023
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.
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.
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.
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.
Commercial and Operations Director at SygmaTel, BlaBla Connect, KnowMe Solutions
Real User
2018-09-25T09:23:00Z
Sep 25, 2018
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!
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.
We are tracking because we have an integrated system. We have some integration with external third parties. We also track the data that we get from external sources. In Postgres, we can handle maybe ten million records per month. We use partitioning and healing features to manage this growth in data. Google Cloud SQL provides fast and very short transactions when modifying our data, using Postgres as our database system across multiple ports. It performs queries for data and handles purchases based on those queries. The scalability with Postgres is impressive. Currently, we are in a beta phase, utilizing three instances. There were issues with write and read instances. Also, there were delays in data synchronization between the write and read columns. When data is written to the write instance, it's not always immediately available in the read instance, causing a delay of up to 20 seconds. We have the right systems to manage the necessary operations. Sometimes, we have one instance for handling requests; at other times, we might have more than two instances. Querying the correct data is fast. However, read queries can be slower due to the large amount of data they need to process. We use additional processing power from more instances to accommodate the required scale. Google Cloud SQL is straightforward. The setup and configuration are easy, and managing the team is simple. We have one dedicated person per week to handle incidents or disturbances in the process and perform additional work. It's enough for maintenance and support. As data accumulates, it's crucial to devise a strategy for managing its volume, which involves using historical tables, archiving, or partitioning. These methods are all useful. As the data volume increases, query execution times can slow down. Therefore, it's imperative to implement an effective indexing strategy. By optimizing indexes, partitioning, and other techniques, queries can be executed more efficiently, even when querying on multiple parameters. There could be two or three read instances. The synchronization between the write and the read is very fast. There are multiple advantages to Google Cloud SQL. Firstly, it operates in the cloud, making it accessible from anywhere. Unlike competitors, Google Cloud SQL is fully integrated into the cloud environment. You can quickly scale your resources up or down according to your needs, growing or decreasing. This flexibility allows you to stay aligned with current demands while optimizing costs. Overall, I rate the solution a nine out of ten.
My organization uses AWS and not Google Cloud SQL for web applications. Instead of Google Cloud SQL, my company uses services from Amazon RDS and Treasure Data's DMP to support my company's data storage for analytics workloads. The features of Google Cloud SQL I find most beneficial for database management stems from the fact that all the employees in our company can access it. I don't know about the impact of the product's scalability in our organization since there is another section in my company that manages it. I don't take care of the maintenance part of the product. I also am not involved in the troubleshooting process related to the product since there is another team in my company that takes care of such areas. There are 20 engineers in my company who take care of the maintenance part of the product. The integration capability of the product with the services offered by Google is very good. The reliability offered by the product is enough for my company. I rate the overall tool a seven out of ten.
I recommend to experience the value of the solution.
My advice to people who are considering using Google Cloud SQl is to consider your budget and performance needs when picking Google Cloud services. If you have a big budget and need high performance, go for Google Cloud SQL. But if you're a small company with budget constraints, use VM instances with databases inside to save money. Overall, I would rate the solution an eight out of ten.
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.
I would rate the solution a seven out of ten. You will need around 10 admins to maintain the tool.
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 would rate this solution an eight out of ten.
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 are a customer and an end-user. I'd rate the solution an eight out of ten.
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.
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.
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.
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.
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!