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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)
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 enhances our AI-driven projects by providing features like query optimization and scalability for efficiently processing large datasets."
"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."
"The solution is easy to use. I am impressed with the tool's features and functionality."
"It is not the cool features that I find valuable, it is the stability of Google Cloud Platform."
"The initial setup is straightforward."
"It supports different databases, like Postgres and MySQL."
"Google Cloud SQL is highly scalable."
"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 is better than the legacy databases, and it is very good with the cloud."
"The speed of it is the most valuable feature."
"The initial setup is very simple and straightforward; it's not overly complex or difficult, and with AWS, implementation is not an issue anymore, so from the user's perspective you just create the database and it's as easy as that."
"It enables us to get work done quickly and get to our data."
"The dynamic structures are the most valuable."
"It's a very elastic solution for the purposes of our systems and the developers appreciate it for software development."
"It can store data as a flat file, similar to a file system."
"It is a great product."
 

Cons

"The overall documentation and the connectors need improvement."
"In my opinion the most vulnerable problem with Google SQL is each SQL node is provided with a public IP address."
"We see latency issues, so we were forced to introduce an in-memory store."
"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."
"They could improve documentation and dashboard stability for efficient user experience and database management."
"The only room for improvement here is that they need to connect to more existing data sources so that it becomes easier for a layman to get a more realistic understanding of what's happening."
"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."
"Sometimes the sharing with third parties or configuring that in Google Cloud SQL is not the most intuitive."
"MongoDB Atlas should add more APIs in their Terraform module because sometimes I find it difficult to find the resources in their Terraform model."
"From an improvement standpoint, MongoDB can improve security."
"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."
"The import and export process needs improvement, i.e., getting in and out. Moving data from other databases into MongoDB, along with indexing, was challenging."
"The speed when combining two documents is concerning."
"The import and export process needs improvement, i.e., getting in and out. Moving data from other databases into MongoDB, along with indexing, was challenging."
"During the configuration, we did some migrations where we had to reindex about 70,000 indexes, which took around an hour. They should improve this and optimize the indexing."
"The product's file storage documentation needs improvement."
 

Pricing and Cost Advice

"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."
"You need to pay extra costs for backup and replication."
"The solution is affordable."
"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."
"While the platform’s pricing may be higher, it aligns with industry standards, considering the quality of service and features provided."
"For me, MongoDB is expensive, but I think it is not so expensive for customers."
"For our service, it was around 300 to 600 euros per month, which was acceptable for our customers."
"Pricing could always be better."
"I have seen the cost, and it was pretty cheap."
"It is too expensive. They need to work on this."
"The solution is fairly priced. I rate the pricing a seven out of ten."
"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."
"MongoDB Atlas is not expensive, and since it's a cloud-based solution, you pay by usage."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
10%
University
9%
Manufacturing Company
7%
Manufacturing Company
11%
Financial Services Firm
11%
Computer Software Company
9%
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.
885,264 professionals have used our research since 2012.