Try our new research platform with insights from 80,000+ expert users

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 (8th)
 

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 setup was straightforward. Just a couple of clicks, and we were done."
"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."
"From a database management perspective, it provides services without the need for me to worry about backups, scaling, or other operational issues."
"Google Cloud SQL is easy to start with and allows me to scale as needed, which is advantageous from a developer perspective."
"Google Cloud SQL is highly scalable."
"Google Cloud SQL enhances our AI-driven projects by providing features like query optimization and scalability for efficiently processing large datasets."
"The initial setup is straightforward."
"I rate MongoDB Atlas a nine out of ten."
"This solution is very helpful due to its ease of use."
"The auto-scaling feature is the most valuable aspect."
"Administering the solution is easy."
"The most valuable feature is the schemaless architecture."
"Scalability is its most valuable feature, as it is pretty simple."
"It's a good solution for NoSQL databases."
"Our databases used to be in-house. Now, they are in the cloud with MongoDB and everything is much easier."
 

Cons

"The monitoring part could be better."
"The customer support should be improved."
"The overall documentation and the connectors need improvement."
"The purging of the data could be better."
"The product's user interface could be more user-friendly to improve the overall user experience."
"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."
"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."
"Google Cloud SQL still needs better connectivity to outside, existing data sources."
"One improvement that I would like to see is a feature to export changes made in the environment, such as creating a new user."
"MongoDB Atlas is effective for unstructured and semi-structured data, but when it comes to OLTP transactions, its performance declines."
"When I edit a document from a document, a lot of clicking is involved, like changing data type manually from a drop-down. It would be super nice if I could just edit the document in a JSON format. The JSON-based document editor should have a multi-language feature. Also, it would be great if there was a connect option from Google Looker Studio."
"We had some edge cases where scalability was an issue where a node went offline, and we had to deal with that."
"I am still new with it, but since I mentioned that I'm using this product for only the last six months and my experience with this product is good thus far, on a scale of one to ten, I would give MongoDB Atlas a six."
"I would like a more comprehensive dashboard."
"The price of the solution should be reduced."
"The product does not have ORM."
 

Pricing and Cost Advice

"You need to pay extra costs for backup and replication."
"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 solution is affordable."
"From a financial perspective, Google Cloud SQL is on the cheaper side."
"The pricing is very much an important factor as to why we use this solution."
"It is not expensive, especially considering the significant reduction in database management time."
"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."
"The pricing and licensing is great."
"We pay for the license on a monthly basis. It's not cheap or expensive. For smaller companies, it's definitely expensive."
"The solution is expensive overall. It does not require a license but if you want the support then you will need to purchase the license. They use a pay-as-you-go model and you are able to receive some discounts by making longer usage commitments."
"The pricing is not that expensive, but it can be, especially when we have deployed it across multiple zones."
"It is an open-source platform."
"I have seen the cost, and it was pretty cheap."
"For our service, it was around 300 to 600 euros per month, which was acceptable for our customers."
report
Use our free recommendation engine to learn which Database as a Service (DBaaS) solutions are best for your needs.
883,692 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
10%
University
8%
Educational Organization
8%
Manufacturing Company
12%
Financial Services Firm
11%
Computer Software 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 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.
883,692 professionals have used our research since 2012.