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Google Cloud Spanner vs Microsoft Azure Cosmos DB comparison

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Comparison Buyer's Guide

Executive SummaryUpdated on Jan 25, 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 Spanner
Ranking in Database as a Service (DBaaS)
8th
Average Rating
9.2
Reviews Sentiment
7.8
Number of Reviews
5
Ranking in other categories
No ranking in other categories
Microsoft Azure Cosmos DB
Ranking in Database as a Service (DBaaS)
4th
Average Rating
8.2
Reviews Sentiment
6.9
Number of Reviews
115
Ranking in other categories
NoSQL Databases (1st), Managed NoSQL Databases (1st), Vector Databases (1st)
 

Mindshare comparison

As of November 2026, in the Database as a Service (DBaaS) category, the mindshare of Google Cloud Spanner is 7.3%, up from 5.7% compared to the previous year. The mindshare of Microsoft Azure Cosmos DB is 4.8%, up from 3.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Database as a Service (DBaaS) Mindshare Distribution
ProductMindshare (%)
Microsoft Azure Cosmos DB4.8%
Google Cloud Spanner7.3%
Other87.9%
Database as a Service (DBaaS)
 

Featured Reviews

LJ
System Architect at UST Global España
Offers good performance to users
The tool lacks to offer AI features. In the future, I would like the product to offer AI features to users. Nowadays, we are creating small acronyms for our SQL Server. We put some templates. If I just put your name and stop it, the entire cloud can be explored, but such features are not there in Google Cloud Spanner. As a layman rather than a developer, if I create a tool or a procedure. If I write a procedure and then when you describe a procedure, a dummy procedure will be written for you, and it will be available for you as a template in SQL Server, but such kind features are not there in Google Cloud Spanner.
Aman-Narang - PeerSpot reviewer
Technical Manager at Infosys
Real-time messaging has transformed customer updates and now powers responsive AI experiences
The primary benefits of Microsoft Azure Cosmos DB include horizontal scalability. The main advantage is that it handles data growth without requiring database redesign when traffic increases. Low latency access is another key benefit, as read and write operations are very fast, which is extremely helpful for real-time applications. Flexibility is also valuable because Microsoft Azure Cosmos DB uses JSON schema format, which contrasts with traditional table schemas that require time-consuming changes. In modernization scenarios where client requirements change rapidly, Microsoft Azure Cosmos DB offers more flexible schema design. High availability is another important feature, as it is well-suited for business-critical systems. My overall experience using Microsoft Azure Cosmos DB with other Azure services shows that it is more flexible compared to SQL Database and more readable because of its JSON format, making it easy to understand. It is more interactive because viewing the Microsoft Azure Cosmos DB schema clearly shows what is happening in the application and what will be achieved. In contrast, SQL requires writing many queries to obtain details, making Microsoft Azure Cosmos DB more suitable and flexible. My team's experience developing with Microsoft Azure Cosmos DB SDKs and APIs has been very comfortable and easy to implement. We are currently migrating .NET applications to Python-based AI solutions using Copilot, where we performed reverse engineering and are moving to forward engineering. We use APIs to connect with Microsoft Azure Cosmos DB and manage database containers and items, performing CRUD operations such as create, delete, and read operations, and querying JSON. We are using REST APIs with Python-based solutions, with a service layer and Microsoft Azure Cosmos DB integration.

Quotes from Members

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

Pros

"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."
"Google Cloud Spanner is stable."
"It is a very scalable solution."
"The solution is stable and reliable."
"The application deployment in the cloud is the best feature of the infrastructure."
"The benefits of Microsoft Azure Cosmos DB were immediate for us."
"I definitely recommend Microsoft Azure Cosmos DB."
"We doubled our productivity with this small application."
"Switching to the cloud significantly improved scalability, flexibility, and uptime."
"We love the ability to land data with Cosmos DB easily. Cosmos is native to Azure, so everything works seamlessly with it. You need good data to have good AI, and Cosmos makes it easy to land the data."
"Our team has found the vCore index to be one of the most valuable features. We have tokenized and vectorized our entire database and stored this data in MongoDB collections with a vCore index, which works like magic for keyword selection."
"Microsoft Azure Cosmos DB is a good solution for distributed application requirements. We can perform multi-modeling."
"One valuable feature of Microsoft Azure Cosmos DB is partitioning. Its performance is very nice."
 

Cons

"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 tool lacks to offer AI features."
"The cost can be a bit high."
"I want to improve the deployment of cameras and surveillance infrastructure."
"The tool needs to improve horizontal scaling."
"Cosmos should be cheaper. We actually intend to stop using it in the near future because the price is too high — and because of the stability issues."
"The model with autoscaling for RU is complicated to optimize RU consumption."
"It would be nice to have more options to ingest the data, for example, more file options or more search options. Currently, you can use JSON, but if there were other file types you can use for data ingestion, that would be nice."
"The integration of the on-premise solution with the cloud can be difficult sometimes."
"I hope they improve the service. Before last year, improvements on Cosmos DB were very slow."
"One area for improvement is the ease of writing SQL queries and stored procedures in Microsoft Azure Cosmos DB. Writing an SQL query and a stored procedure on top of that is a little challenging."
"I do not have any specific suggestions for improvements at the moment. However, having more AI capabilities in the future would be beneficial."
"We would like to see advancements in AI with the ability to benchmark vector search capabilities, ensuring it answers questions accurately. During our initial implementation, we faced challenges with indexing and sorting, which are natively available in other offerings but required specific configurations in Cosmos."
 

Pricing and Cost Advice

"Google Cloud Spanner is an expensive solution."
"It is expensive."
"The solution is expensive."
"Price-wise, I heard that Google Cloud Spanner is on the higher side."
"Cosmos DB is a highly cost-optimized solution when used correctly."
"Its pricing is not bad. It is good."
"Most customers like the flexibility of the pricing model, and it has not been an issue. They can start small, and the cost grows with adoption, allowing efficient management of the budget. Its pricing model has not been a concern at all for any of our customers. They understand it. It is simple enough to understand. Oftentimes, it is hard to forecast the RUs, but, in general, it has been fine."
"The pricing for Cosmos DB has improved, particularly with the new pricing for Autoscale."
"Cosmos DB is a managed offering, so its cost is understandably higher."
"Because of the lack of understanding about RUs, the costs become unpredictable. It sometimes goes over the budget."
"Our experience with the pricing and setup cost is that it aligns with what we expect based on the pricing we see. However, I would absolutely like it to be less if possible."
"Its pricing structure is quite flexible."
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Top Industries

By visitors reading reviews
Financial Services Firm
23%
Manufacturing Company
9%
Healthcare Company
9%
Comms Service Provider
7%
Financial Services Firm
11%
Outsourcing Company
11%
Legal Firm
10%
Manufacturing Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business36
Midsize Enterprise24
Large Enterprise60
 

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 Microsoft Azure Cosmos DB?
I have knowledge about the pricing, setup cost, and licensing aspect of Microsoft Azure Cosmos DB.
What needs improvement with Microsoft Azure Cosmos DB?
Microsoft Azure Cosmos DB could improve cost and performance management to be more straightforward, particularly for teams managing workloads with variable traffic. More detailed and proactive reco...
What is your primary use case for Microsoft Azure Cosmos DB?
My main use case for Microsoft Azure Cosmos DB is to support application workloads that require a highly scalable, low latency NoSQL database. I primarily use it to store and manage semi-structured...
 

Also Known As

Google Spanner
Microsoft Azure DocumentDB, MS Azure Cosmos DB
 

Overview

 

Sample Customers

Streak, Optiva, Mixpanel
TomTom, KPMG Australia, Bosch, ASOS, Mercedes Benz, NBA, Zero Friction, Nederlandse Spoorwegen, Kinectify
Find out what your peers are saying about Google Cloud Spanner vs. Microsoft Azure Cosmos DB and other solutions. Updated: November 2026.
920,929 professionals have used our research since 2012.