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Google Cloud SQL vs MongoDB Atlas comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jan 11, 2026

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Google Cloud SQL
Ranking in Database as a Service (DBaaS)
6th
Ranking in Database Management Systems (DBMS)
9th
Average Rating
8.2
Reviews Sentiment
6.9
Number of Reviews
23
Ranking in other categories
Relational Databases Tools (19th)
MongoDB Atlas
Ranking in Database as a Service (DBaaS)
3rd
Ranking in Database Management Systems (DBMS)
4th
Average Rating
8.4
Reviews Sentiment
6.9
Number of Reviews
50
Ranking in other categories
Managed NoSQL Databases (3rd), AI Software Development (10th)
 

Mindshare comparison

As of March 2026, in the Database as a Service (DBaaS) category, the mindshare of Google Cloud SQL is 7.6%, down from 16.5% compared to the previous year. The mindshare of MongoDB Atlas is 12.1%, down from 14.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Database as a Service (DBaaS) Mindshare Distribution
ProductMindshare (%)
MongoDB Atlas12.1%
Google Cloud SQL7.6%
Other80.3%
Database as a Service (DBaaS)
 

Featured Reviews

Prathap Sankar - PeerSpot reviewer
Analytics Delivery Manager at Tredence Inc.
Gain control and flexibility with customizable tools but has slower performance
I am majorly working in Google Cloud SQL for building my applications Google Cloud SQL provides complete customization options, along with a dashboarding tool and a comprehensive suite of tools that can be used to customize and build any application needed. The deployment model allows for…
Laksiri Bala - PeerSpot reviewer
DB Architect / Consultant at Virtusa Global
Room for improvement in data handling leads to enhanced cost-effective data management performance
It would be beneficial if MongoDB Atlas could better support OLTP aspects and data frames, as well as enhance its capabilities for data pipelines and visualization dashboards. Furthermore, supporting the medallion architecture could be a valuable addition, and incorporating improved spatial and vector handling for geographical data could make it more competitive. Enhancing vector processing for AI capabilities would also be critical.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"Ease of management and the ability to oversee the statistics of your SQL."
"The solution is easy to use. I am impressed with the tool's features and functionality."
"The valuable feature of Google Cloud SQL is its high availability option. The product is stable."
"What I like the most about Google Cloud SQL is that it handles the management, which allows us to concentrate on our applications."
"Google Cloud SQL provides complete customization options, along with a dashboarding tool and a comprehensive suite of tools that can be used to customize and build any application needed."
"It supports different databases, like Postgres and MySQL."
"It is not the cool features that I find valuable, it is the stability of Google Cloud Platform."
"The deployment model allows for significant control and flexibility."
"The most useful feature is the management of the backup."
"The solution has a very intuitive user interface."
"The price of MongoDB Atlas is reasonable, which is why many organizations, including mine, are opting for it."
"The initial setup of MongoDB Atlas is straightforward...It is a scalable solution."
"The most beneficial MongoDB features for our workload are the ability to scale up and down using automatic sharding and clustering."
"I am impressed with the tool's integrations."
"Our databases used to be in-house. Now, they are in the cloud with MongoDB and everything is much easier."
"There are many valuable features, but scalability stands out. It can scale across zones. You can define multiple nodes. They have also partnered with AWS, offering great service with multiple features, including built-in backup, all under the same roof, without the need for external tools."
 

Cons

"Google Cloud SQL still needs better connectivity to outside, existing data sources."
"To create a seamless data integration, the title integration of these databases with the data integration platforms is essential. This is what we would like to have in a future release."
"The product's user interface could be more user-friendly to improve the overall user experience."
"The most vulnerable problem with Google SQL is that while you can customize your access control list, it provides you with a public IP address."
"The customer support should be improved."
"The performance compared to AWS is not as fast, and the technical support could be better as they don't have a dedicated team, but mostly AI handles the support now."
"It is hard to do logging with the solution."
"The overall documentation and the connectors need improvement."
"The UI is not currently designed in a manner to make it possible for a non-technical person or a layman to update the database easily."
"I am not an expert on what improvements could be made to MongoDB."
"One improvement that I would like to see is a feature to export changes made in the environment, such as creating a new user."
"The product's file storage documentation needs improvement."
"A few areas that we have noticed as being problematic with the MongoDB Atlas include user access to the platform. Currently, it is difficult to restrict and control what actions a user can perform within the solution, which poses a challenge from an internal auditing perspective."
"The biggest challenge we all have is an application layer level. One node is sitting in the APAC region, another node is sitting in the US and UK region. The seamless replication has to be lightning fast, but we haven't tested the scalability yet."
"We had some bad trainers when we first came onboard and would rate them fairly low. They did not seem staffed properly to fulfill the training services that they offered."
"MongoDB Atlas should add more APIs in their Terraform module because sometimes I find it difficult to find the resources in their Terraform model."
 

Pricing and Cost Advice

"While the platform’s pricing may be higher, it aligns with industry standards, considering the quality of service and features provided."
"It is not expensive, especially considering the significant reduction in database management time."
"The solution is affordable."
"You need to pay extra costs for backup and replication."
"It's really cheap. It wouldn't be more than, I believe it's around 50 euro per month for running a cloud SQL."
"The pricing is very much an important factor as to why we use this solution."
"From a financial perspective, Google Cloud SQL is on the cheaper side."
"The pricing is acceptable for enterprise tier."
"Pricing could always be better."
"It is too expensive. They need to work on this."
"For our service, it was around 300 to 600 euros per month, which was acceptable for our customers."
"The tool is free since it's an open-source product."
"The solution is fairly priced."
"I have seen the cost, and it was pretty cheap."
"In my previous company, the product allowed use to build a database in a highly regulated environment with the ability to get distributed storage. We used MongoDB as a distributed storage to set up this environment for a critical business application with millions of dollars."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
10%
University
9%
Educational Organization
7%
Manufacturing Company
11%
Financial Services Firm
11%
Computer Software Company
10%
Comms Service Provider
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business9
Midsize Enterprise4
Large Enterprise9
By reviewers
Company SizeCount
Small Business24
Midsize Enterprise10
Large Enterprise20
 

Questions from the Community

What is your experience regarding pricing and costs for Google Cloud SQL?
We have set up automated patch management for Google Cloud SQL, and it does on a daily basis what needs to be done, so it is pretty good overall for maintaining our database security.
What needs improvement with Google Cloud SQL?
Sometimes the sharing with third parties or configuring that in Google Cloud SQL is not the most intuitive. From a user perspective, if Google Cloud SQL integrated AI directly into the query so tha...
What is your primary use case for Google Cloud SQL?
I have been using Google Cloud SQL for two or three years since I started.
What do you like most about MongoDB Atlas?
There are many valuable features, but scalability stands out. It can scale across zones. You can define multiple nodes. They have also partnered with AWS, offering great service with multiple featu...
What is your experience regarding pricing and costs for MongoDB Atlas?
Pricing-wise, MongoDB Atlas has a pay-as-you-go strategy. The documentation for MongoDB is very good; I have learned multiple things through reading it. The free tier is M0 for $0, which is suitabl...
What needs improvement with MongoDB Atlas?
An improvement I can suggest for MongoDB Atlas is achieving even faster query execution and smoother application performance. In terms of scalability, it handles system growth without failure, but ...
 

Also Known As

No data available
Atlas, MongoDB Atlas (pay-as-you-go)
 

Overview

 

Sample Customers

BeDataDriven, CodeFutures, Daffodil, GenieConnect, KiSSFLOW, LiveHive, SulAm_rica, Zync
Wells Fargo, Forbes, Ulta Beauty, Bosch, Sanoma, Current (a Digital Bank), ASAP Log, SBB, Zebra Technologies, Radial, Kovai, Eni, Accuhit, Cognigy, and Payload.
Find out what your peers are saying about Google Cloud SQL vs. MongoDB Atlas and other solutions. Updated: March 2026.
884,797 professionals have used our research since 2012.