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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

"Ease of management and the ability to oversee the statistics of your SQL."
"The valuable feature of Google Cloud SQL is its high availability option. The product is stable."
"My suggestion to anyone thinking about this solution is to jump into it head-first!"
"Google Cloud SQL enhances our AI-driven projects by providing features like query optimization and scalability for efficiently processing large datasets."
"The implementation part of the product was easy."
"The most valuable feature for us is the Postgres on Google Cloud SQL since it supports most of the features we need."
"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."
"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 dynamic structures are the most valuable."
"The solution is easily scalable and manageable. Tools can be easily added to the solution."
"MongoDB Atlas was explicitly designed to support IoT applications. Many databases offer features tailored for IoT use cases."
"The initial setup of MongoDB Atlas is straightforward...It is a scalable solution."
"The key feature of MongoDB Atlas that has been helpful for us is the ease of deploying new databases."
"The auto-scaling feature is the most valuable aspect."
"Object-based data storing capability and managing non-structured data capability are the most valuable features of MongoDB Atlas."
"It's a good solution for NoSQL databases."
 

Cons

"They could improve documentation and dashboard stability for efficient user experience and database management."
"Google's technical support is good, but they tend to never reopen a case and to send us snippets from the publicly available documentation. It's not as helpful as you would expect, not just for Google Cloud SQL but for all of Google Cloud products."
"I would like to see better integration with all the different tools on the platform."
"When discussing media files, such as images and audio files, stored in Google Cloud, concerns about handling large amounts of data arise."
"I would appreciate more flexibility with specific extensions applicable to engines like PostgreSQL."
"The customer support should be improved."
"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."
"Based on its own habitat, it's not ACID compliant. If it had an ACID compliant option, it would be more useful for database administration."
"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 would say pricing is an area where MongoDB Atlas could improve."
"The installation was straightforward except for the network hardware because it was a little complicated to make the connection with our VPC on AWS."
"They could explore ways to facilitate deploying MongoDB containers within the platform."
"The product's data aggregation feature needs to work faster."
"The product does not have ORM."
 

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."
"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 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."
"We pay for the license on a monthly basis. It's not cheap or expensive. For smaller companies, it's definitely expensive."
"We pay for a license."
"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."
"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."
"MongoDB Atlas is more cost-effective than Amazon DocumentDB. It also has a pay-as-you-go pricing model. Apart from the standard licensing cost, you must also pay to get MongoDB Atlas technical support, which is 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."
"It is an open-source platform."
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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.