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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)
3rd
Average Rating
8.4
Reviews Sentiment
6.9
Number of Reviews
50
Ranking in other categories
Managed NoSQL Databases (3rd), AI Software Development (5th)
 

Mindshare comparison

As of February 2026, in the Database as a Service (DBaaS) category, the mindshare of Google Cloud SQL is 7.8%, down from 16.5% compared to the previous year. The mindshare of MongoDB Atlas is 12.3%, down from 15.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Database as a Service (DBaaS) Market Share Distribution
ProductMarket Share (%)
MongoDB Atlas12.3%
Google Cloud SQL7.8%
Other79.9%
Database as a Service (DBaaS)
 

Featured Reviews

VD
Database Engineer at Springer Nature
Migration to cloud eases management but needs better support for high I/O operations
Google Cloud SQL needs to improve its support for high-end I/O operations. On-prem systems with high I/O capabilities perform better, as Google Cloud SQL takes more time to handle the same tasks. There is also difficulty in changing the time zone after the database is set up. Moreover, some features available in MSSQL on-prem are missing on Google Cloud SQL, affecting migration potential.
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

"My suggestion to anyone thinking about this solution is to jump into it head-first!"
"Google Cloud SQL is highly scalable."
"It's SQL. SQL is so easy if you know something about databases. It's easy to learn."
"From a database management perspective, it provides services without the need for me to worry about backups, scaling, or other operational issues."
"The setup was straightforward. Just a couple of clicks, and we were done."
"Google Cloud SQL enhances our AI-driven projects by providing features like query optimization and scalability for efficiently processing large datasets."
"Google Cloud SQL is easy to start with and allows me to scale as needed, which is advantageous from a developer perspective."
"It is not the cool features that I find valuable, it is the stability of Google Cloud Platform."
"The most useful feature is the management of the backup."
"Administering the solution is easy."
"Object-based data storing capability and managing non-structured data capability are the most valuable features of MongoDB Atlas."
"The solution has a very intuitive user interface."
"It's flexible. We don't need to have a solid upstream availability failover, and everything is seamless in Atlas."
"The solution is easily scalable and manageable. Tools can be easily added to the solution."
"As a tester, it was easy to validate data, access data, make active run queries against it, and retrieve data from it."
"I am impressed with the tool's integrations."
 

Cons

"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 most challenging part is dealing with legacy data from your old systems and migrating it into the new setup, but once you've completed the data migration, it becomes quite convenient to use."
"I am yet to explore a lot of features that are present in this solution. However, it would be good if more documentation is available for this solution. This would help us in preparing for the certification exam and understand it better. Currently, we don't have much documentation. We do the labs for 20 or 25 minutes, but we can't capture and download anything."
"The overall documentation and the connectors need improvement."
"When discussing media files, such as images and audio files, stored in Google Cloud, concerns about handling large amounts of data arise."
"In the case of Google, they need to work on a more easy interface for users."
"For data analysis, the AI area of the product has certain shortcomings where improvements are required."
"The product's user interface could be more user-friendly to improve the overall user experience."
"It would be better if there were more integration capabilities with other products."
"I would like the solution to offer more integration capabilities since it is an area where the solution lacks."
"The price of the solution should be reduced."
"MongoDB Atlas should support containerization."
"There are some features that could be useful for the customers I work with, which are related to migration from on-prem to the cloud."
"The installation was straightforward except for the network hardware because it was a little complicated to make the connection with our VPC on AWS."
"The cost needs improvement."
"We need improved query performance."
 

Pricing and Cost Advice

"It is not expensive, especially considering the significant reduction in database management time."
"You need to pay extra costs for backup and replication."
"The solution is affordable."
"While the platform’s pricing may be higher, it aligns with industry standards, considering the quality of service and features provided."
"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."
"It's really cheap. It wouldn't be more than, I believe it's around 50 euro per month for running a cloud SQL."
"For our service, it was around 300 to 600 euros per month, which was acceptable for our customers."
"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."
"It is too expensive. They need to work on this."
"The solution is fairly priced."
"The pricing is acceptable for enterprise tier."
"Comparing the price between the MongoDB and Microsoft SQL Server, we are using the enterprise edition of Microsoft SQL Server, which is more expensive than MongoDB."
"I am using the free version of the solution."
"I have seen the cost, and it was pretty cheap."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
11%
Educational Organization
9%
University
8%
Financial Services Firm
12%
Computer Software Company
11%
Manufacturing Company
11%
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 Business23
Midsize Enterprise11
Large Enterprise20
 

Questions from the Community

What do you like most about Google Cloud SQL?
The implementation part of the product was easy.
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 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: January 2026.
882,594 professionals have used our research since 2012.