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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)
6th
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)
8th
Average Rating
8.4
Reviews Sentiment
7.2
Number of Reviews
50
Ranking in other categories
Managed NoSQL Databases (3rd), AI Software Development (8th)
 

Mindshare comparison

As of January 2026, in the Database as a Service (DBaaS) category, the mindshare of Google Cloud SQL is 8.5%, down from 16.8% compared to the previous year. The mindshare of MongoDB Atlas is 12.7%, 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 Atlas12.7%
Google Cloud SQL8.5%
Other78.8%
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

"The solution is easy to use. I am impressed with the tool's features and functionality."
"I found its storage and security to be the most valuable. It was a good experience. It is also very stable and scalable, and its support is perfect."
"Google Cloud SQL is very easy to use and easy to set up; it brings the benefits of being simple to perform queries, store data that I needed to store, and extract data when I needed to extract it quite quickly, without having to set up a full database and queries around it."
"The initial setup is straightforward."
"The most valuable feature for us is the Postgres on Google Cloud SQL since it supports most of the features we need."
"This is a stable solution and offers good performance."
"Google Cloud SQL enhances our AI-driven projects by providing features like query optimization and scalability for efficiently processing large datasets."
"What I like the most about Google Cloud SQL is that it handles the management, which allows us to concentrate on our applications."
"It can store data as a flat file, similar to a file system."
"It is a scalable solution because we use quite a lot of data, and it handles it well."
"I am impressed with the tool's integrations."
"The stability and performance are great. The high availability feature is great. Moreover, I am happy with the automated backup and restore functionality."
"It's a good solution for NoSQL databases."
"Being schemaless is what I like best about MongoDB Atlas."
"The solution is easily scalable and manageable. Tools can be easily added to the solution."
"The cloud-based nature of this solution makes it flexible and scalable."
 

Cons

"I would appreciate more flexibility with specific extensions applicable to engines like PostgreSQL. This would enhance the capabilities of Google Cloud SQL."
"Google Cloud SQL needs to improve its support for high-end I/O operations."
"It is hard to do logging with the solution."
"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."
"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."
"They could improve documentation and dashboard stability for efficient user experience and database management."
"The purging of the data could be better."
"The only thing that could be better is the pricing."
"I would say pricing is an area where MongoDB Atlas could improve."
"The initial configuration fine-tuning for performance can be time-consuming."
"I would like a better dashboard. It could be made a bit more user friendly."
"If it could be cheaper, that would make us happy."
"Querying a dataset is not very intuitive, so I think that it can be improved."
"The product's data aggregation feature needs to work faster."
"In the past, MongoDB offered more features for free, but now it's quite limited. The free version is limited, and you need to pay extra to fully utilize it. The pricing could be improved."
"The UI application for MongoDB crashes a lot, so we would have to use a third-party plugin to make it work."
 

Pricing and Cost Advice

"From a financial perspective, Google Cloud SQL is on the cheaper side."
"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."
"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."
"For me, MongoDB is expensive, but I think it is not so expensive for customers."
"The price of MongoDB Atlas is highly expensive to use and maintain. They are taking advantage of the users with such a high price."
"Pricing could always be better."
"It is an open-source platform."
"The price of MongoDB Atlas is highly affordable."
"I am using the free version of the solution."
"For our service, it was around 300 to 600 euros per month, which was acceptable for our customers."
"The pricing is good. We originally chose it over DynamoDB because of the pricing."
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Top Industries

By visitors reading reviews
Financial Services Firm
15%
Computer Software Company
11%
Educational Organization
9%
University
8%
Computer Software Company
13%
Financial Services Firm
12%
Manufacturing Company
12%
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 Enterprise10
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?
I have no idea about the pricing or setup cost with MongoDB Atlas.
What needs improvement with MongoDB Atlas?
I would say pricing is an area where MongoDB Atlas could improve.
 

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.
881,082 professionals have used our research since 2012.