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 (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

"Google Cloud SQL is easy to start with and allows me to scale as needed, which is advantageous from a developer perspective."
"It directly provides robust data safety. It also offers various other storage options, such as Google Cloud Storage. These services ensure data security and redundancy. Furthermore, it includes different storage classes, allowing flexible data management tailored to specific needs."
"The most valuable feature for us is the Postgres on Google Cloud SQL since it supports most of the features we need."
"The product is scalable."
"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."
"Ease of management and the ability to oversee the statistics of your SQL."
"This is a stable solution and offers good performance."
"Google Cloud SQL is highly scalable."
"It can store data as a flat file, similar to a file system."
"It's a good solution for NoSQL databases."
"MongoDB Atlas is a platform as a service and it has proven to be particularly valuable due to its self-managing nature. This has allowed us to minimize the amount of time and effort required to manage it, as it effectively manages itself. Additionally, it is a complete solution when looking at its features."
"The solution has a very intuitive user interface."
"The auto-scaling feature is the most valuable aspect."
"The solution is easily scalable and manageable. Tools can be easily added to the solution."
"I find MongoDB Atlas highly scalable and easy to use, with very good support."
"It is a scalable solution because we use quite a lot of data, and it handles it well."
 

Cons

"Sometimes the sharing with third parties or configuring that in Google Cloud SQL is not the most intuitive."
"I would like to see better availability of the product in different regions. It should also improve the security with encryption."
"The product's user interface could be more user-friendly to improve the overall user experience."
"The only thing that could be better is the pricing."
"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."
"For data analysis, the AI area of the product has certain shortcomings where improvements are required."
"Google Cloud SQL needs to improve its support for high-end I/O operations."
"I would like to see better integration with all the different tools on the platform."
"The cost needs improvement. The product is good, but the cost that we paid for it is expensive, so it wasn't that valuable."
"The product's file storage documentation needs improvement."
"It would be better if there were more integration capabilities with other products."
"The installation was straightforward except for the network hardware because it was a little complicated to make the connection with our VPC on AWS."
"From an improvement standpoint, MongoDB can improve security."
"We had some edge cases where scalability was an issue where a node went offline, and we had to deal with that."
"MongoDB Atlas should add more APIs in their Terraform module because sometimes I find it difficult to find the resources in their Terraform model."
"It would be great if it were easier to integrate MongoDB Atlas with AWS services. Technical support for MongoDB Atlas could be better."
 

Pricing and Cost Advice

"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."
"You need to pay extra costs for backup and replication."
"From a financial perspective, Google Cloud SQL is on the cheaper side."
"The solution is affordable."
"It is not expensive, especially considering the significant reduction in database management time."
"While the platform’s pricing may be higher, it aligns with industry standards, considering the quality of service and features provided."
"The tool is free since it's an open-source product."
"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."
"We're currently using the Atlas for the night and don't require a license. However, it can be a problem if you want to use their enterprise environment. Then you need to purchase the license."
"The price of MongoDB Atlas is highly expensive to use and maintain. They are taking advantage of the users with such a high price."
"I have seen the cost, and it was pretty cheap."
"MongoDB Atlas is not expensive, and since it's a cloud-based solution, you pay by usage."
"The solution is fairly priced."
"We pay for the license on a monthly basis. It's not cheap or expensive. For smaller companies, it's definitely expensive."
report
Use our free recommendation engine to learn which Database as a Service (DBaaS) solutions are best for your needs.
884,797 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
11%
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.