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Google Cloud SQL vs MongoDB Atlas comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Aug 12, 2024

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)
4th
Average Rating
8.2
Reviews Sentiment
6.8
Number of Reviews
22
Ranking in other categories
No ranking in other categories
MongoDB Atlas
Ranking in Database as a Service (DBaaS)
3rd
Average Rating
8.4
Reviews Sentiment
7.4
Number of Reviews
48
Ranking in other categories
Managed NoSQL Databases (6th)
 

Mindshare comparison

As of May 2025, in the Database as a Service (DBaaS) category, the mindshare of Google Cloud SQL is 16.2%, down from 18.3% compared to the previous year. The mindshare of MongoDB Atlas is 14.2%, down from 15.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Database as a Service (DBaaS)
 

Featured Reviews

Prathap Sankar - PeerSpot reviewer
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
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."
"The initial setup is straightforward."
"Ease of management and the ability to oversee the statistics of your SQL."
"My suggestion to anyone thinking about this solution is to jump into it head-first!"
"The valuable feature of Google Cloud SQL is its high availability option. The product is stable."
"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."
"It's SQL. SQL is so easy if you know something about databases. It's easy to learn."
"The most valuable feature for us is the Postgres on Google Cloud SQL since it supports most of the features we need."
"The cloud-based nature of this solution makes it flexible and scalable."
"It's flexible. We don't need to have a solid upstream availability failover, and everything is seamless in Atlas."
"The stability and performance are great. The high availability feature is great. Moreover, I am happy with the automated backup and restore functionality."
"Administering the solution is easy."
"The key feature of MongoDB Atlas that has been helpful for us is the ease of deploying new databases."
"MongoDB is a NoSQL tool."
"It enables us to get work done quickly and get to our data."
"It is nice because our developers create tables whenever they need to sync data."
 

Cons

"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."
"The monitoring part could be better."
"The purging of the data could be better."
"I would appreciate more flexibility with specific extensions applicable to engines like PostgreSQL."
"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."
"When discussing media files, such as images and audio files, stored in Google Cloud, concerns about handling large amounts of data arise."
"It is hard to do logging with the solution."
"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 product's data aggregation feature needs to work faster."
"Searching and browsing through the collection must be made easier."
"From an improvement standpoint, MongoDB can improve security."
"The speed when combining two documents is concerning."
"One improvement that I would like to see is a feature to export changes made in the environment, such as creating a new user."
"I would like a better dashboard. It could be made a bit more user friendly."
"Querying a dataset is not very intuitive, so I think that it can be improved."
"I would like the solution to offer more integration capabilities since it is an area where the solution lacks."
 

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."
"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."
"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 purchasing process through the AWS Marketplace was very good."
"MongoDB Atlas is not expensive, and since it's a cloud-based solution, you pay by usage."
"The pricing is not that expensive, but it can be, especially when we have deployed it across multiple zones."
"The pricing is acceptable for enterprise tier."
"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."
"I am using the free version of the solution."
"The solution is fairly priced. I rate the pricing a seven out of ten."
"For our service, it was around 300 to 600 euros per month, which was acceptable for our customers."
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Top Industries

By visitors reading reviews
Financial Services Firm
15%
Computer Software Company
13%
University
8%
Retailer
8%
Computer Software Company
20%
Financial Services Firm
15%
Comms Service Provider
7%
Healthcare Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

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?
The cost is expensive, especially for services like BigQuery, which charge based on query operations. We pay as we use, with no fixed cost.
What needs improvement with Google Cloud SQL?
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. T...
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?
The price of MongoDB Atlas is reasonable, which is why many organizations, including mine, are opting for it.
What needs improvement with MongoDB Atlas?
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, supporti...
 

Also Known As

No data available
Atlas
 

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: April 2025.
849,686 professionals have used our research since 2012.