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Google Cloud Spanner vs MongoDB Atlas comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jul 2, 2025

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 Spanner
Ranking in Database as a Service (DBaaS)
8th
Average Rating
9.0
Reviews Sentiment
7.8
Number of Reviews
5
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
49
Ranking in other categories
Managed NoSQL Databases (7th)
 

Mindshare comparison

As of July 2025, in the Database as a Service (DBaaS) category, the mindshare of Google Cloud Spanner is 4.7%, up from 3.6% compared to the previous year. The mindshare of MongoDB Atlas is 13.3%, down from 15.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Database as a Service (DBaaS)
 

Featured Reviews

Ethan Lo - PeerSpot reviewer
A stable and scalable relational database that ensures a return on investment for its users
The most valuable feature of the solution is its scalability. Scalability comes with two options, among which Google Cloud Spanner can scale horizontally, compared to other relational databases that scale vertically. You can change Google Cloud Spanner's resource configuration, which is done through processing units. Suppose you set up Google Cloud Spanner initially with a hundred processing units, and then you run out of resources since your database used too much CPU. In the aforementioned scenario, you can scale up or down and face no downtime in the production phase. The solution's features are important when running a company twenty-four hours, seven days a week.
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

"The application deployment in the cloud is the best feature of the infrastructure."
"We can scale the solution if we need to."
"The most valuable feature of the solution is its scalability. Scalability comes with two options, among which Google Cloud Spanner can scale horizontally, compared to other relational databases that scale vertically."
"It is a very scalable solution."
"Google Cloud Spanner is stable."
"As a tester, it was easy to validate data, access data, make active run queries against it, and retrieve data from it."
"The features that I have found most valuable include the very easy integrations. The integrations are fantastic. I have not faced any challenges from the integration standpoint."
"The price of MongoDB Atlas is reasonable, which is why many organizations, including mine, are opting for it."
"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."
"MongoDB Atlas was explicitly designed to support IoT applications. Many databases offer features tailored for IoT use cases."
"MongoDB Atlas is very easy to use and user-friendly, and you get what you're paying for."
"The product provides quick transaction service, high availability, and efficient scalability features."
"It can store data as a flat file, similar to a file system."
 

Cons

"The tool needs to improve horizontal scaling."
"The tool lacks to offer AI features."
"I want to improve the deployment of cameras and surveillance infrastructure."
"Google came up with something called Cloud Spanner Emulator, which fails to work like the real product if I want to develop some code and run a database locally on my machine."
"The cost can be a bit high."
"A few areas that we have noticed as being problematic with the MongoDB Atlas include user access to the platform. Currently, it is difficult to restrict and control what actions a user can perform within the solution, which poses a challenge from an internal auditing perspective."
"We had some bad trainers when we first came onboard and would rate them fairly low. They did not seem staffed properly to fulfill the training services that they offered."
"It would be better if there were more integration capabilities with other products."
"They could explore ways to facilitate deploying MongoDB containers within the platform."
"The UI application for MongoDB crashes a lot, so we would have to use a third-party plugin to make it work."
"The product does not have ORM."
"Querying a dataset is not very intuitive, so I think that it can be improved."
"The UI is not currently designed in a manner to make it possible for a non-technical person or a layman to update the database easily."
 

Pricing and Cost Advice

"The solution is expensive."
"Google Cloud Spanner is an expensive solution."
"It is expensive."
"Price-wise, I heard that Google Cloud Spanner is on the higher side."
"The purchasing process through the AWS Marketplace was very good."
"Pricing could always be better."
"The pricing and licensing is great."
"It is too expensive. They need to work on this."
"The pricing is not that expensive, but it can be, especially when we have deployed it across multiple zones."
"The pricing is good. We originally chose it over DynamoDB because of the pricing."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
22%
Computer Software Company
13%
Retailer
9%
Manufacturing Company
8%
Computer Software Company
18%
Financial Services Firm
15%
Manufacturing Company
8%
Comms Service Provider
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What is your primary use case for Google Cloud Spanner?
Google Cloud Spanner has all the features of a traditional relational database, including schemas, SQL queries, ACID transactions, and provides excellent integration and monitoring tools as well as...
What is your experience regarding pricing and costs for Google Cloud Spanner?
Price-wise, I heard that Google Cloud Spanner is on the higher side. I am not sure if this is a rumor or if it's fake news, but I believe that having BigQuery and GCP together could be a little cos...
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?
There is nothing about MongoDB Atlas I would like to improve or any weak points at this time. I have not thought through what other features I would like to see included in future updates. MongoDB ...
 

Also Known As

Google Spanner
Atlas, MongoDB Atlas (pay-as-you-go)
 

Overview

 

Sample Customers

Streak, Optiva, Mixpanel
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 Spanner vs. MongoDB Atlas and other solutions. Updated: July 2025.
860,825 professionals have used our research since 2012.