Google Cloud SQL vs. PostgreSQL

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Google Cloud SQL
Score 8.9 out of 10
N/A
Google Cloud SQL is a database-as-a-service (DBaaS) with the capability and functionality of MySQL.
$0
per core hour
PostgreSQL
Score 8.3 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 SQLPostgreSQL
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 SQLPostgreSQL
Free Trial
YesNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsPricing 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 SQLPostgreSQL
Features
Google Cloud SQLPostgreSQL
Database-as-a-Service
Comparison of Database-as-a-Service features of Product A and Product B
Google Cloud SQL
9.3
Ratings
7% above category average
PostgreSQL
-
Ratings
Automatic software patching9.60 Ratings00 Ratings
Database scalability9.50 Ratings00 Ratings
Automated backups9.70 Ratings00 Ratings
Database security provisions9.50 Ratings00 Ratings
Monitoring and metrics8.20 Ratings00 Ratings
Automatic host deployment9.00 Ratings00 Ratings
Best Alternatives
Google Cloud SQLPostgreSQL
Small Businesses
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
InfluxDB
InfluxDB
Score 8.8 out of 10
Medium-sized Companies
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
SQLite
SQLite
Score 9.6 out of 10
Enterprises
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
SQLite
SQLite
Score 9.6 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Google Cloud SQLPostgreSQL
Likelihood to Recommend
9.5
(0 ratings)
8.0
(0 ratings)
Likelihood to Renew
9.0
(0 ratings)
9.0
(0 ratings)
Usability
8.0
(0 ratings)
8.0
(0 ratings)
Availability
-
(0 ratings)
9.0
(0 ratings)
Performance
-
(0 ratings)
7.0
(0 ratings)
Support Rating
6.4
(0 ratings)
9.3
(0 ratings)
Implementation Rating
-
(0 ratings)
9.0
(0 ratings)
Ease of integration
6.6
(0 ratings)
-
(0 ratings)
Product Scalability
-
(0 ratings)
8.0
(0 ratings)
User Testimonials
Google Cloud SQLPostgreSQL
Likelihood to Recommend
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.
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PostgreSQL is ideal for handling databases that contain large volumes of information due to its efficiency, speed and above all because of the good management it makes of our resources, it also behaves very well in distributed environments of high demand, if you want a database of stable data and excellent performance PostgreSQL is one of the best.
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Pros
  • Very easy to use and migrate existing database systems to Google Cloud SQL system
  • Easy to query with real-time query assessment as well as processing metrics to help optimize the queries
  • No need to learn any other querying language (like in Hadoop ecosystem), as SQL works pretty fine
  • Easy-to-use GCP portal to type in queries and see the results on the screen (no need to go on command line )
  • Easy to set up
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  • Advanced spatial capabilities by using PostGIS extension
  • Very fast data processing and support of native ANSI SQL language syntax allows maintaining capability and scalability of database
  • Fast data aggregation, even by SQL or stored routines/functions
  • Well documented, free for use, great community. A lot of examples, and for this reason - lesser threshold for junior developers to start with
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Cons
  • Increasing support for more database engines may enable a wider range of application needs to be met.
  • Implementing and updating cutting-edge security features on a constant basis.
  • Streamlining and enhancing the tools for transferring data to Google Cloud SQL from on-premises databases or other cloud providers.
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  • The performance of PostgreSQL has been enhanced through the years, but always is better to have as much performance as we can.
  • The replication services could be done directly within the database, and more easily.
  • The Object Orientation of the Database could be extended, and albeit it manages inheritance of tables, and accepts XML and JSON as primary types, it would be wonderful if one could attach methods more easily to tables (to make them more like classes), and instances (rows for example).
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Likelihood to Renew
It fits the current needs and bandwith of out lean organization.
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As a needed software for day to day development activities
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Usability
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.
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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.
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Reliability and Availability
No answers on this topic
PostgreSQL's availability is top notch. Apart from connection time-out for an idle user, the database is super reliable.
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Performance
No answers on this topic
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.
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Support Rating
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.
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AWS, Heroku, and Digital Ocean all provide Postgres-as-a-service, where you pretty much never need to administrate it yourself but they do it for you. The Postgres community also has developed awesome and reasonably priced extensions, such as Citus DB and CockroachDB in case you need additional support for running it. If you need documentation, Postgres's docs are super thorough and their official forms are active.
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Online Training
No answers on this topic
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.
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Implementation Rating
No answers on this topic
The online documentation of the PostgreSQL product is elaborate and takes users step by step.
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Alternatives Considered
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.
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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 over its competitors in that it can adapt or configure third-party programs, applications, or settings.
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Scalability
No answers on this topic
The DB is reliable, scalable, easy to use and resolves most DB needs
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Return on Investment
  • The first one is it's performance is very good and it comes up with different solution.
  • Security can be improved for external resources or the schemas which are selected in it.
  • It can be more fragile so one can use it in the business purposes and this will make it a great product.
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  • Easy to administer so our DevOps team has only ever used minimal time to setup, tune, and maintain.
  • Easy to interface with so our Engineering team has only ever used minimal time to query or modify the database. Getting the data is straightforward, what we do with it is the bigger concern.
  • It's free. You can't beat that.
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ScreenShots

Google Cloud SQL Screenshots

Screenshot of migrating to a fully managed database solution - Self-managing a database, such as MySQL, PostgreSQL, or SQL Server, can be inefficient and expensive, with significant effort around patching, hardware maintenance, backups, and tuning. Migrating to a fully managed solution can be done using a Database Migration Service with minimal downtime.Screenshot of data-driven application development - Cloud SQL accelerates application development via integration with the larger ecosystem of Google Cloud services, Google partners, and the open source community.