Google Cloud SQL is a database-as-a-service (DBaaS) with the capability and functionality of MySQL.
$0
per core hour
PostgreSQL
Score 8.8 out of 10
N/A
PostgreSQL (alternately Postgres) is a free and open source object-relational database system boasting over 30 years of active development, reliability, feature robustness, and performance. It supports SQL and is designed to support various workloads flexibly.
N/A
Pricing
Google Cloud SQL
PostgreSQL
Editions & Modules
License - Express
$0
per core hour
License - Web
$0.01134
per core hour
Storage - for backups
$.08
per month per GB
HA Storage - for backups
$.08
per month per GB
Storage - HDD storage capacity
$.09
per month per GB
License - Standard
$0.13
per core hour
Storage - SSD storage capacity
$.17
per month per GB
HA Storage - HDD storage capacity
$.18
per month per GB
HA Storage - SSD storage capacity
$.34
per month per GB
License - Enterprise
$0.47
per core hour
Memory
$5.11
per month per GB
HA Memory
$10.22
per month per GB
vCPUs
$30.15
per month per vCPU
HA vCPUs
$60.30
per month per vCPU
No answers on this topic
Offerings
Pricing Offerings
Google Cloud SQL
PostgreSQL
Free Trial
Yes
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
Pricing varies with editions, engine, and settings, including how much storage, memory, and CPU you provision. Cloud SQL offers per-second billing.
—
More Pricing Information
Community Pulse
Google Cloud SQL
PostgreSQL
Considered Both Products
Google Cloud SQL
Verified User
Anonymous
Chose Google Cloud SQL
Our use case was mainly within the Google Cloud ecosystem, so this service was of high value where all of our sub-infra for a project was right there in one place. We no longer had to maintain separate dashboard for monitoring just because our compute and database were on …
It is easy to connect Google Cloud SQL with the Compute Engine, Cloud Run, BigQuery, or PubSub. The connection inside the Google infrastructure is much more secured and fast when they are in same zone/region, so never faced any issues. The documentation is excellent to connect …
I've used supabase and can say that Google Cloud SQL is a lot more hands off. They just run an instance for you and don't do much more than that. Which is exactly what we wanted. If you want something that is truly fully managed and abstracted then I guess that would be a …
Given this is a hosted solution, database a service it helps in removing the effort of maintaining these databases manually. Eases out the pain of upgrading, applying security patches and keeping things running without having to worry about missed changes. The database can be …
As I used Google Cloud SQL it's performance is very good and it's ui ux is as per the user demand. Apart from it the backend is very strong which makes it more usable tools as it gives or run the query in very minimal time. Yes there has to be some work on security and …
I 100% prefer Google Cloud SQL over Amazon Aurora in terms of ease of use and clarity in terms of understanding how the autoscaling is going to work. Connecting to the database directly is also much more straightforward.
In our experience, we were down for almost a day, because Database Engineers at Rackspace weren't able to understand or provide a solution, and when they did, they had to recreate the database from the scratch. On a server, this is time consuming. When we faced a similar …
BigQuery is a great analytical database and is generally our first choice for large analytical workloads. While its performance and throughput far outperforms Google Cloud SQL but it supports a far limited dialets of SQL. Generally a significant rewrite will be needed for …
Setting up or migrating Google Cloud SQL is easy as compared to AWS. It has a good monitoring and logging mechanism and a good user interface which makes it easy to navigate.It also has a pay as you go pricing which makes it easier to reduce cost. Google Cloud SQL offers …
Actually Google Cloud SQL is similar to them, the difference is which engine each supports e.g. there's no managed Oracle DB in Google Cloud SQL but as long as you don't need Oracle, Google Cloud SQL should suffice and give you great user experience and performance. You also …
Google SQL was great as a first SQL provision. It quickly enabled the apps to be built and scaled as needed for a while. It was robust and adaptable as needed and easy to export as needed when ready, depending on growth. Cost-wise, it's a good choice and requires little …
Unlike other products, Google Cloud SQL has very flexible features that allow it to be selected for a free trial account so that the product can be analyzed and tested before purchasing it. Integration capabilities with most of the web services tools are easier regarding Google …
When comparing cost, Google Cloud SQL typically offers a more straightforward and versatile plan than Azure SQL Database. Cloud SQL for PostgreSQL is a serverless solution provided by Google Cloud SQL that automatically modifies resources according to workload. For customers …
- AWS RDS and Aurora is a just a notch above Google Cloud SQL as it provide boost in performance when required - Google Cloud SQL Mysql Engine is Cloud based and better than native Mysql as it provides management of the server out of box - Compared to a MongoDB it has a low …
At first, we choose Google Cloud SQL only for demo purposes. It is so easy to set up and It is fully managed. we have worked with Azure SQL as well but Google SQL is more simple to use and It fully secure, reliable, provides high availability, and very Low Latency.
Easier learning, simple features and settings with a very user-friendly application environment and flexible prices make Google Cloud [SQL] a pioneering option over competitors
My expirence with other solutions is very limited, but what I saw/heard is, that on Azure the managed MS SQL Server is said to be more flexible and you can use it in a serverless-ish fashion. But on the other hand, PostgresSQL is still strong regarding its efficiency. And in my …
Being open source, PostgreSQL offers the highest performance among its peers. It has a strong support community where we can find solutions to most of the queries. It's suited for GIS (Geospatial) based applications, making it unique from its peers. There are fewer databases …
PostgreSQL holds it own against both these options. Some of these DBs are in play for certain needs but the majority are PostgreSQL because of cost and operational performance.
In my experience using all of these products over many years, PostgreSQL is better than any of them in reliability, performance, productivity, cost, scalability and interoperability across operating systems.
MySQL is an Oracle product which has in itself some known issues due to that (support, contract terms). Based on my knowledge, PostgreSQL support everything that MySQL support (syntax wise) and it adds more improvements and syntaxes that make the life of database engineers and …
First It's open source and it's cost-effective compared to other databases.PostgreSQL can be easily integrated with numerous platforms. It is well known and appreciated so relying on it as our system database can be easily accepted by our customers. And if your developing a …
For our use cases, PostgreSQL is just as feature rich as other options, costs less, and is simple to get up and running. There is also a plethora of documentation to support it which makes it a great option for a small scale startup without needing high levels of expertise to …
In this case, Postgres is preferred because it handles large data sets and requires fewer hardware resources than its competitor, MySQL. Compared to PostgreSQL, Microsoft products are excellent, but the installation process for MS SQL is lengthy. PostgreSQL has an advantage …
I've been using different databases for the past 20 years, solutions like MS SQL Server, MySQL, MariaDB, Interbase, Firebird, DB2, etc., and by using them I wasn't able to be neither close to the performance PostgreSQL deliver. Also, it is one of the most popular databases on …
Although the competition between the different databases is increasingly aggressive in the sense that they provide many improvements, new functionalities, compatibility with complementary components or environments, in some cases it requires that it be followed within the same …
We evaluated both PostgreSQL and MySQL, two popular open source relational databases. While they are very similar in most areas, PostgreSQL's reliability and performance won us over, plus it has much better support from cloud vendors we also work with.
Postgres stacks up just [fine] along the other big players in the RDBMS world. It's very popular for a reason. It's very close to mySQL in terms of cost and features - I'd pick either solution and be just as happy. Compared to Oracle it is a MUCH cheaper solution that is just …
A free corporate professional product. Who does not want to have such a thing, we hesitated because we did not know the product before and frankly we did not want it at first. But when we give it a chance, it has been running smoothly for years.
When we were originally evaluating Redshift we ran into some issue with dates. Either way, Postgres is a better choice than Redshift because it avoids vendor lockin. We ended up choosing Postgres over MySQL because it was easier at the time to get a hosted Postgres cluster up …
As I have been telling all along, PostgreSQL is much cheaper compared to the other RDBMS solutions. It has got better performance with some of the application services that we are using and is easy to maintain. Overall, we are satisfied migrating to PostgreSQL database clusters.
Much more mature and stable when compared to MySQL with features such as MVCC, complex subquery plans, ORDBMS, and NoSQL support. With Oracle retaining rights to MySQL its future as an open database is less secure and is no longer in the hands of the community. PostgreSQL also …
Its main characteristic is the integrity of the data. In addition, being free software, it has no costs associated with its license, which allows the number of installations to be scaled without problems.
The technical staff quickly learns about its installation, configuration …
Both Oracle and MS-SQL database option fell when we evaluated the effect on our overall solution cost to our customers. customer examine the overall cost of the solution they buy, selecting Oracle or MS-SQL would leave less money in our pockets. We are Linux based solutions and …
PostgrPostgreSQL as a transaction db engine against oracle and sql server works well. TPM wise compared to MySQL and MariaDB, on an evan scale. SQL function supports, far outweighs compared to MySQL and MariaDB. PG Extensions allow for flexibiltity and scalability. Allows …
We selected PostgreSQL due to the number of employees who have used it in the past. The data consistency guarantees. The multiple transaction isolation levels support.
PostgreSQL outperforms every other option. It is faster, more flexible, more reliable, easier to maintain, and more consistent in behaviour than any of the other offerings.
The main reason for select PostgreSQL against MS SQL Server Express edition is the necessity to use open-source platform, without any issues for licensing, client licensing, etc. etc, which is usually follows developers and project managers when they start to use products and …
Does what it promises well, for instance, as a sidecar for the main enterprise data warehouse. However, I would not recommend using it as the main data warehouse, particularly due to the heavy business logic, as other dedicated tools are more suitable for ensuring scalable operations in terms of change management and multi-developer adjustments.
Based on my experience, PostgreSQL is exactly what I imagine when thinking of a relational database: it is fast for querying and intuitive (if the underlying relations have been well written) and its writes are also efficient. Of course you need to know that a relational database is what you need, for example I would not recommend it if you have a lot of unstructured data that have no way to create a relation from and if you need to run heavy aggregations over your data, as it is not where PostgreSQL would shine.
The stability it offers, its speed of response and its resource management is excellent even in complex database environments and with low-resource machines.
The large amount of resources it has in addition to the many own and third-party tools that are compatible that make productivity greatly increase.
The adaptability in various environments, whether distributed or not, [is a] complete set of configuration options which allows to greatly customize the work configuration according to the needs that are required.
The excellent handling of referential and transactional integrity, its internal security scheme, the ease with which we can create backups are some of the strengths that can be mentioned.
The query syntax for JSON fields is unwieldy when you start getting into complex queries with many joins.
I wish there was a distinction (a flag) you could set for automated scripts vs working in the psql CLI, which would provide an 'Are you sure you want to do X?' type prompt if your query is likely to affect more than a certain number of rows. Especially on updates/deletes. Setting the flag in the headless(scripted) flow would disable the prompt.
Better documentation around JSON and Array aggregation, with more examples of how the data is transformed.
As with other cloud tools, users must learn a new terminology to navigate the various tools and configurations, and understand Google Cloud's configuration structure to perform even the most basic operations. So the learning curve is quite steep, but after a few months, it gets easier to maintain.
Postgresql is the best tool out there for relational data so I have to give it a high rating when it comes to analytics, data availability and consistency, so on and so forth. SQL is also a relatively consistent language so when it comes to building new tables and loading data in from the OLTP database, there are enough tools where we can perform ETL on a scalable basis.
The data queries are relatively quick for a small to medium sized table. With complex joins, and a wide and deep table however, the performance of the query has room for improvement.
GCP support in general requires a support agreement. For small organizations like us, this is not affordable or reasonable. It would help if Google had a support mechanism for smaller organizations. It was a steep learning curve for us because this was our first entry into the cloud database world. Better documentation also would have helped.
There are several companies that you can contract for technical support, like EnterpriseDB or Percona, both first level in expertise and commitment to the software.
But we do not have contracts with them, we have done all the way from googling to forums, and never have a problem that we cannot resolve or pass around. And for dozens of projects and more than 15 years now.
The online training is request based. Had there been recorded videos available online for potential users to benefit from, I could have rated it higher. The online documentation however is very helpful. The online documentation PDF is downloadable and allows users to pace their own learning. With examples and code snippets, the documentation is great starting point.
Unlike other products, Google Cloud SQL has very flexible features that allow it to be selected for a free trial account so that the product can be analyzed and tested before purchasing it. Integration capabilities with most of the web services tools are easier regarding Google Cloud SQL with its nature and support.
In my experience using all of these products over many years, PostgreSQL is better than any of them in reliability, performance, productivity, cost, scalability and interoperability across operating systems.
Improved integration with Google Cloud, we have set up some automations with Google Workspace, and we have noticed that the raw data sharing between them is very fast as compared to using some other managed database, not sure why.
Due to some downtime during maintenance, we had to set up a relatively small service which ingested the data while this went down and dumped it when it came back up. So this was a negative impact on our ROI, since now we had to remedy this downtime against the same profit margins
It was cheaper than the legacy aws service since we needed large database instances