Google Cloud SQL vs MongoDB Atlas comparison

Google and MongoDB are both solutions in the Database as a Service (DBaaS) category. Google is ranked #4 with an average rating of 7.8, while MongoDB is ranked #3 with an average rating of 8.4. Google holds a 16.5% mindshare in DS, compared to MongoDB’s 14.5% mindshare. Additionally, 100% of Google users are willing to recommend the solution, compared to 96% of MongoDB users who would recommend it.

Google Cloud SQL

Read 22 Google Cloud SQL reviews

3,161 Views
2,874 Comparison Views

100% willing to recommend

MongoDB Atlas

Read 48 MongoDB Atlas reviews

3,963 Views
2,403 Comparison Views

96% willing to recommend

Google Cloud SQL

MongoDB Atlas

Comparison Buyer's Guide

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Executive SummaryUpdated on Aug 12, 2024

Google Cloud SQL and MongoDB Atlas compete in the managed database services category. Google Cloud SQL has the upper hand in SQL database management, while MongoDB Atlas is better suited for NoSQL databases with flexible schema design.

Features: Google Cloud SQL offers automated backups, high availability, and seamless integration with other Google Cloud services. MongoDB Atlas includes rich querying capabilities, horizontal scaling, and global clusters.

Room for Improvement: Google Cloud SQL needs better cost management tools and more comprehensive logging features. MongoDB Atlas can improve support responsiveness and documentation clarity.

Ease of Deployment and Customer Service: Google Cloud SQL is known for its straightforward deployment process and robust customer service. MongoDB Atlas is easy to deploy but has slightly lower marks for customer service.

Pricing and ROI: Google Cloud SQL is more affordable, especially for smaller projects, with good ROI through efficient resource management. MongoDB Atlas, while offering significant features, is seen as relatively more expensive.

To learn more, read our detailed Google Cloud SQL vs. MongoDB Atlas Report (Updated: March 2025).

Buyer's Guide

Google Cloud SQL vs. MongoDB Atlas

March 2025

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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

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

Ranking in other categories

Managed NoSQL Databases (6th)

Mindshare comparison

As of April 2025, in the Database as a Service (DBaaS) category, the mindshare of Google Cloud SQL is 16.5%, down from 18.6% compared to the previous year. The mindshare of MongoDB Atlas is 14.5%, down from 14.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Database as a Service (DBaaS)

Featured Reviews

Prathap Sankar

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…

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Laksiri Bala

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.

Read full review

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The deployment model allows for significant control and flexibility."

"The most valuable feature for us is the Postgres on Google Cloud SQL since it supports most of the features we need."

"The valuable feature of Google Cloud SQL is its high availability option. The product is stable."

"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 product is scalable."

"Google Cloud SQL is highly scalable."

"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."

"This is a stable solution and offers good performance."

More Google Cloud SQL pros

"Being schemaless is what I like best about MongoDB Atlas."

"The most valuable feature of MongoDB Atlas is it's seamless when working with a lot of different systems. Additionally, it is able to adjust the data based on the data being received."

"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."

"The initial setup of MongoDB Atlas is straightforward...It is a scalable solution."

"MongoDB Atlas was explicitly designed to support IoT applications. Many databases offer features tailored for IoT use cases."

"The solution has a very intuitive user interface."

"MongoDB Atlas is a database that is quite fast, stable, and reliable."

More MongoDB Atlas pros

Cons

"The only thing that could be better is the pricing."

"To create a seamless data integration, the title integration of these databases with the data integration platforms is essential. This is what we would like to have in a future release."

"In the case of Google, they need to work on a more easy interface for users."

"Google Cloud SQL needs to improve its support for high-end 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."

"When discussing media files, such as images and audio files, stored in Google Cloud, concerns about handling large amounts of data arise."

"For data analysis, the AI area of the product has certain shortcomings where improvements are required."

"The overall documentation and the connectors need improvement."

More Google Cloud SQL cons

"MongoDB Atlas should add more APIs in their Terraform module because sometimes I find it difficult to find the resources in their Terraform model."

"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."

"Querying a dataset is not very intuitive, so I think that it can be improved."

"The UI application for MongoDB crashes a lot, so we would have to use a third-party plugin to make it work."

"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."

"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 initial setup is not too difficult but can be somewhat tricky."

"The price of the solution should be reduced."

More MongoDB Atlas cons

Pricing and Cost Advice

"You need to pay extra costs for backup and replication."

"From a financial perspective, Google Cloud SQL is on the cheaper side."

"While the platform’s pricing may be higher, it aligns with industry standards, considering the quality of service and features provided."

"It is not expensive, especially considering the significant reduction in database management time."

"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 solution is affordable."

"The pricing is very much an important factor as to why we use this solution."

"In my previous company, the product allowed use to build a database in a highly regulated environment with the ability to get distributed storage. We used MongoDB as a distributed storage to set up this environment for a critical business application with millions of dollars."

"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 pricing is not that expensive, but it can be, especially when we have deployed it across multiple zones."

"We pay for a license."

"The pricing and licensing is great."

"The pricing is acceptable for enterprise tier."

"I have seen the cost, and it was pretty cheap."

"I am using the free version of the solution."

More MongoDB Atlas pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

15%

Computer Software Company

13%

University

Retailer

Computer Software Company

19%

Financial Services Firm

16%

Comms Service Provider

Manufacturing Company

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.

See all answers

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.

See all answers

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...

See all answers

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...

See all answers

What is your experience regarding pricing and costs for MongoDB Atlas?

The pricing is quite acceptable and scalable. For our service, it was around 300 to 600 euros per month, which was acceptable for our customers. We could scale up for better performance and scale d...

See all answers

What needs improvement with MongoDB Atlas?

I am not an expert on what improvements could be made to MongoDB. The service is continually evolving with new features while maintaining reasonable pricing, making it attractive for developers.

See all answers

Comparisons

Microsoft Azure SQL Database vs Google Cloud SQL

Compared 41% of the time

Amazon RDS vs Google Cloud SQL

Compared 36% of the time

Oracle Database as a Service vs Google Cloud SQL

Compared 6% of the time

Google Cloud Spanner vs Google Cloud SQL

Compared 3% of the time

Oracle Exadata Cloud at Customer vs Google Cloud SQL

Compared 2% of the time

More Google Cloud SQL Competitors

Amazon RDS vs MongoDB Atlas

Compared 45% of the time

Microsoft Azure SQL Database vs MongoDB Atlas

Compared 16% of the time

MongoDB vs MongoDB Atlas

Compared 7% of the time

Upstash vs MongoDB Atlas

Compared 5% of the time

Amazon DocumentDB vs MongoDB Atlas

Compared 5% of the time

More MongoDB Atlas Competitors

Product Reports

Buyer's Guide

Google Cloud SQL

March 2025

Download Google Cloud SQL product report

Buyer's Guide

MongoDB Atlas

March 2025

Download MongoDB Atlas product report

Also Known As

No data available

Atlas

Overview

Google Cloud SQL is a fully-managed database service that makes it easy to set up, maintain, manage, and administer your relational PostgreSQL and MySQL databases in the cloud. Google Cloud SQL offers high performance, scalability, and convenience. Hosted on Google Cloud Platform, Cloud SQL provides a database infrastructure for applications running anywhere.

Google

MongoDB Atlas offers a cloud-based database service known for speed, scalability, ease of use, and flexibility. Its robust features and advanced security measures support various business needs, making it ideal for unstructured data management.

MongoDB Atlas maximizes data handling capabilities by providing a seamless integration and high availability environment. The platform's schemaless architecture and rich query support make it suitable for complex data processing. With cloud-based infrastructure, deployment and maintenance are simplified, serving sectors such as healthcare, finance, and more. Organizations benefit from autoscaling, clustering, and APIs for effective project management. Continuous improvements in user experience, cost-effectiveness, query performance, and security are expected to meet evolving expectations.

What are the most important features?

Speed: Optimized for fast data handling and processing.
Scalability: Adapts to growing data needs without hassle.
Ease of Use: User-friendly interface for efficient navigation.
Flexibility: Supports unstructured data with ease.
Integration: Seamlessly connects with cloud environments.
High Availability: Ensures uninterrupted data access and operations.
Advanced Security: Protects data with robust security measures.
Schemaless Architecture: Enables dynamic data structure management.
Rich Query Support: Facilitates complex queries and analytics.

What benefits and ROI should be considered?

Easy Deployment: Streamlines the setup process in cloud environments.
Efficient Project Management: APIs and tools enhance workflow.
Cost-Effectiveness: Potential for more flexible pricing models.
Data Management: Automates backups and supports clustering.
Advanced Tools: Enables comprehensive data processing capabilities.

MongoDB Atlas is widely implemented in industries such as healthcare, finance, and technology. It serves applications requiring high availability and scalability, handling tasks from patient data management to real-time analytics. With its adaptable infrastructure, Atlas supports diverse use cases from IoT integration to transactional processing in cloud environments.

MongoDB

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.

Buyer's Guide

Google Cloud SQL vs. MongoDB Atlas

March 2025

Free Report: Google Cloud SQL vs. MongoDB Atlas

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