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Google Cloud SQL is a popular Google Cloud database service, offering managed versions of MySQL, PostgreSQL, and Microsoft SQL Server. Google Cloud pricing for the SQL service is broken down into CPU and memory costs, licensing, storage, and networking costs.
In this post we’ll explain the pricing structure, provide pricing examples and explain the limitations of the Cloud SQL service. We’ll also show how NetApp Cloud Volumes ONTAP can help reduce Google Cloud SQL pricing and storage footprint by up to 70%.
In this article, you will learn:
- Google Cloud SQL Server pricing
- Google Cloud MySQL pricing
- Google Cloud PostgreSQL pricing
- Google Cloud SQL limitations
- Google Cloud SQL pricing optimization with Cloud Volumes ONTAP
Google Cloud SQL Server Pricing
Google Cloud SQL for SQL Server is composed of the following elements — CPU and memory, Storage, Network, and Licensing. Below we provide a summary of the main Google Cloud SQL pricing options for the us-central1 region.
For additional and up-to-date Google Cloud SQL pricing options, see the official pricing page.
CPU and memory costs
Google Cloud provides discounts for sustained use on all the below costs.
|
vCPUs |
$0.0590 per vCPU |
|
Memory |
$0.0100 per GB |
|
HA vCPUs |
$0.1180 per vCPU |
|
HA Memory |
$0.0200 per GB |
Google Cloud charges a per-hour rate for the software license of SQL Server, depending on the product edition you want to use.
| Enterprise license |
$0.47 per hour |
|
Standard license |
$0.13 per hour |
|
Web license |
$0.01134 per hour |
|
Express license |
Free |
Storage and network costs are the same for all variations of Google Cloud SQL — SQL Server, MySQL, and PostgreSQL.
|
SSD storage |
$0.170 per GB/month |
|
Backups |
$0.080 per GB/month |
Google Cloud also offers highly available storage at a higher price.
Network costs
|
Network Ingress |
Free |
|
IPv4 Addresses |
$0.010 per hour while idle |
|
Egress to Google Compute Engine |
Free |
|
Egress to Other Google Products |
$0.12/GB |
|
Egress to Internet using Cloud Interconnect |
$0.05/GB |
|
Egress to Internet without Cloud Interconnect |
$0.19/GB |
Google Cloud MySQL Pricing
The MySQL service is charged per instance. Below we show the regular hourly cost for six common instances. There are many more instance types and additional pricing options for highly available instances, as well as discounts for sustained use.
|
Machine Type |
Virtual CPUs |
RAM (GB) |
Maximum Storage (GB) |
Maximum Connections |
Price / hour |
|
db-f1-micro |
Shared |
0.6 |
3,062 |
250 |
$0.0150 |
|
db-n1-standard-4 |
4 |
15 |
30,720 |
4,000 |
$0.3860 |
|
db-n1-standard-64 |
64 |
240 |
30,720 |
4,000 |
$6.1770 |
|
db-n1-highmem-16 |
16 |
104 |
30,720 |
4,000 |
$2.0120 |
|
db-n1-highmem-96 |
96 |
624 |
30,720 |
4,000 |
$12.0720 |
Google Cloud MySQL storage and networking costs are identical to Google Cloud SQL Server above.
Google Cloud PostgreSQL Pricing
Below are instance prices for PostgreSQL. All Google Cloud PostgreSQL instances have shared CPUs (there are no dedicated virtual CPUs).
|
Shared-Core Machine Type |
RAM (GB) |
Maximum Storage (GB) |
Price / hour |
|
db-f1-micro* |
0.6 |
3,062 |
$0.0150 |
|
db-g1-small* |
1.7 |
3,062 |
$0.0500 |
|
HA db-f1-micro* |
0.6 |
3,062 |
$0.0300 |
|
HA db-g1-small* |
1.7 |
3,062 |
$0.1000 |
If you need more power, you can buy a customizable amount of CPUs and memory. There are discounts for sustained use.
|
vCPUs |
$0.0590 per vCPU |
|
Memory |
$0.0100 per GB |
|
HA vCPUs |
$0.1180 per vCPU |
|
HA Memory |
$0.0200 per GB |
Storage and networking
Google Cloud MySQL storage and networking costs are identical to those for Google Cloud SQL Server above.
Google Cloud SQL Limitations
When using Cloud SQL, you are also subject to certain limits that are not automatically replenished. Some of these limits are configurable while others are fixed. Below is a breakdown of the limits you face.
Configurable limits
Below you can see an overview of your configurable limits:
|
|
Limitations |
Can you increase limits? |
|
Instances per project |
Allowed up to 40 instances per project |
Yes, by filing a support case |
|
MySQL |
The number of default concurrent connections is determined by machine type. The limits range from 250 to 4,000. |
Yes, but you are recommended to use the default limits.* |
|
PostgreSQL |
The number of default concurrent connections is determined by machine type. The limits range from 25 to 1,000. |
Yes, but you are recommended to use the default limits.*
Your default limit is determined by the number of cores you select. |
|
SQL Server |
The number of user connections is determined by your SQL Server version and the limitations placed by applications and hardware.
The default maximum is 32,767. |
Yes, but requires the use of SQL Server Management Studio or Transact-SQL. |
*If you configure using the max_connections flag you may forfeit your SLA coverage.
Fixed limits
Below you can see an overview of your fixed limits:
|
|
Limitations |
|
Cloud SQL storage limits |
Cloud SQL storage is limited to a maximum of 30,720GB.
For MySQL instances, the true limit is determined by your machine type. For PostgreSQL and SQL Server instances, your limit is determined by whether you are using shared or dedicated vCPUs. |
|
Cloud SQL storage options |
You can choose SSD or HDD. |
|
App Engine Limits |
You are allowed up to 100 concurrent connections to each instance. However, this is restricted to 60 if you are running PHP 5.5 apps. |
For more details, you can see the Cloud SQL documentation here.
Google Cloud SQL Pricing Optimization with Cloud Volumes ONTAP
NetApp Cloud Volumes ONTAP, the leading enterprise-grade storage management solution, delivers secure, proven storage management services on AWS, Azure and Google Cloud. Cloud Volumes ONTAP supports up to a capacity of 368TB, and supports various use cases such as file services, databases, DevOps or any other enterprise workload, with a strong set of features including high availability, data protection, storage efficiencies, Kubernetes integration, and more.
In particular, Cloud Volumes ONTAP helps in addressing database workloads challenges in the cloud, and filling the gap between your cloud-based database capabilities and the public cloud resources it runs on.
