Google Cloud Spanner vs Microsoft Azure Cosmos DB comparison

Google and Microsoft are both solutions in the Database as a Service (DBaaS) category. Google is ranked #8 with an average rating of 10.0, while Microsoft is ranked #4 with an average rating of 8.3. Google holds a 7.2% mindshare in DS, compared to Microsoft’s 4.4% mindshare. Additionally, 100% of Google users are willing to recommend the solution, compared to 95% of Microsoft users who would recommend it.

Google Cloud Spanner

Read 5 Google Cloud Spanner reviews

1,281 Views
1,217 Comparison Views

100% willing to recommend

Microsoft Azure Cosmos DB

Read 109 Microsoft Azure Cosmos DB reviews

10,499 Views
1,575 Comparison Views

95% willing to recommend

Google Cloud Spanner

Microsoft Azure Cosmos DB

Comparison Buyer's Guide

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Executive SummaryUpdated on Jan 25, 2026

Microsoft Azure Cosmos DB and Google Cloud Spanner are competing in the realm of global scalability, low latency, and high availability databases. Cosmos DB appears to have the upper hand due to its versatile multi-model support and broader integration capabilities.

Features:Cosmos DB supports multiple models beyond traditional SQL, including MongoDB, Cassandra, and Gremlin. It offers a multi-model database, high read and write capabilities, and seamless integration with Azure services. Spanner offers consistent, globally-distributed transactions and strong schema management. It supports horizontal scalability and is designed for SQL-centric workloads, making it ideal for complex applications requiring strict SQL compliance.

Room for Improvement:Cosmos DB could benefit from enhanced SQL query performance and reducing complexity in data modeling for high consistency scenarios. It may also improve standard SQL compliance. Spanner's support for non-relational data types could be expanded, along with simplifying architecture requirements for ease of use in non-expert teams. Additionally, improving compatibility with non-Google Cloud services could enhance its versatility.

Ease of Deployment and Customer Service:Cosmos DB integrates easily with Azure services, simplifying deployment with extensive documentation and support. Spanner requires expertise in SQL and knowledge of its architecture for optimal setup. Google's support network is efficient, especially for users deeply integrated within Google Cloud.

Pricing and ROI:Cosmos DB's consumption-based pricing suits dynamic workloads, presenting potentially lower initial setup costs. For dynamic integrations, it promises an appealing ROI. Spanner's higher pricing reflects its consistent performance and scalability, offering better ROI for enterprises focused on transaction integrity and global consistency.

To learn more, read our detailed Google Cloud Spanner vs. Microsoft Azure Cosmos DB Report (Updated: February 2026).

Buyer's Guide

Google Cloud Spanner vs. Microsoft Azure Cosmos DB

February 2026

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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 Spanner

Ranking in Database as a Service (DBaaS)

8th

Average Rating

9.2

Reviews Sentiment

7.8

Number of Reviews

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

109

Ranking in other categories

NoSQL Databases (2nd), Managed NoSQL Databases (1st), Vector Databases (1st)

Mindshare comparison

As of February 2026, in the Database as a Service (DBaaS) category, the mindshare of Google Cloud Spanner is 7.2%, up from 4.0% compared to the previous year. The mindshare of Microsoft Azure Cosmos DB is 4.4%, up from 1.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Database as a Service (DBaaS) Market Share Distribution
Product	Market Share (%)
Microsoft Azure Cosmos DB	4.4%
Google Cloud Spanner	7.2%
Other	88.4%

Database as a Service (DBaaS)

Featured Reviews

LijomonJose

System Architect at UST Global EspaÃ±a

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.

Read full review

reviewer2724105

Senior Director of Product Management at a tech vendor with 1,001-5,000 employees

Provides super sharp latency, excellent availability, and the ability to effectively manage costs across different tenants

For integrating Microsoft Azure Cosmos DB with other Azure products or other products, there are a couple of challenges with the current system. Right now, the vectors are stored as floating-point numbers within the NoSQL document, which makes them inefficiently large. This leads to increased storage space requirements, and searching through a vast number of documents in the vector database becomes quite costly in terms of RUs. While the integration works well, the expense associated with it is relatively high. I would really like to see a reduction in costs for their vector search, as it is currently on the expensive side. The areas for improvement in Microsoft Azure Cosmos DB are vector pricing and vector indexing patterns, which are unintuitive and not well described. I would also like to see the parameters of Fleet Spaces made more powerful, as currently, it's somewhat lightweight. I believe they've made those changes intentionally to better understand the cost model. However, we would like to take a more aggressive approach in using it. One of the most frustrating aspects of Microsoft Azure Cosmos DB right now is that you can only store one vector per document. Additionally, you must specify the configuration of that vector when you create an instance of Microsoft Azure Cosmos DB. Once the database is set up, you can't change the vector configuration, which is incredibly limiting for experimentation. You want the ability to try different settings and see how they perform, as there are numerous use cases for storing more than one vector in a document. While interoperability within the vector database is acceptable—for example, I can search for vectors—I still desire a richer set of configuration options.

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 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."

"We can scale the solution if we need to."

"Google Cloud Spanner is stable."

"It is a very scalable solution."

"The application deployment in the cloud is the best feature of the infrastructure."

"The peace of mind that Microsoft Azure Cosmos DB provides regarding global distribution is invaluable."

"The availability and latency of Azure Cosmos DB are excellent."

"The best feature about Microsoft Azure Cosmos DB is its interface, which is awesome for accessing data."

"The most valuable features for our organization with Azure Cosmos DB are multi-master capability for applications, automatic failover ensuring high availability, scalability, support for multiple data models, and low-latency access."

"The solution's read capacity and write access functions are very fast so users don't have to wait when fetching or displaying data on a screen."

"The most valuable feature of Microsoft Azure Cosmos DB is its real-time analytics capabilities, which allow for turnaround times in milliseconds."

"The best feature of Microsoft Azure Cosmos DB is the replication all over the world."

"The most valuable feature of Microsoft Azure Cosmos DB is its ability to handle concurrency and consistency."

More Microsoft Azure Cosmos DB pros

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 cost can be a bit high."

"I want to improve the deployment of cameras and surveillance infrastructure."

"The tool lacks to offer AI features."

"The tool needs to improve horizontal scaling."

"It should offer a simple user interface for querying Microsoft Azure Cosmos DB."

"Once you create a database, it calls the container, and then items show up. A better description and more guidance would help because the first time I created it, I didn't understand that a container is similar to a table in SQL."

"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."

"The cost is a concern. Microsoft Azure Cosmos DB did not decrease our total cost of ownership. From the standpoint of the old way of doing DBA operations, it did, but our cloud cost increased significantly."

"The initial setup was difficult."

"The challenge for us is always scale."

"If we have a lot of data, doing a real-time vector search is a performance challenge because the search happens over a large dataset. It consumes more time."

"The customer service is lacking. We have a premier support agreement, but support is hit and miss."

More Microsoft Azure Cosmos DB cons

Pricing and Cost Advice

"It is expensive."

"Price-wise, I heard that Google Cloud Spanner is on the higher side."

"The solution is expensive."

"Google Cloud Spanner is an expensive solution."

"This cost model is beneficial because it allows for cost control by limiting resource units (RUs), which is ideal. However, for our needs, we can't engage with their minimum pricing, which ranges from 100 to 1,000 RUs. At the bare minimum, we need to use 4,000 RUs for a customer. I would like to find a way to gain some advantages from the lowest tier, particularly the ability to scale down if necessary. It would be helpful to have more flexibility in cost management at the lower end."

"Its price is very good for the basic stuff. When you go to a more complicated use case, especially when you need replication and availability zones, it gets a little costly."

"The pricing and licensing model was initially difficult to understand, but as soon as I learned what was going on and how it was priced, it was pretty easy."

"We are not consuming so much yet since we are at the beginning of using this solution. I would rate the pricing of Microsoft Azure Cosmos DB a six out of ten."

"Cosmos DB is a managed offering, so its cost is understandably higher."

"Microsoft Azure Cosmos DB pricing is based on RUs. Reading 1 KB document costs one RU, whereas writing one document costs five RUs. Pricing for querying depends on the complexity of the query. If you increase the document size, it will automatically increase the RU cost."

"Microsoft Azure Cosmos DB's licensing costs are monthly."

"Cosmos DB is expensive, and the RU-based pricing model is confusing. Although they have a serverless layer, there are deficiencies in what I can define and assign to a database. Estimating infrastructure needs is not straightforward, making it challenging to manage costs."

More Microsoft Azure Cosmos DB pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

20%

Computer Software Company

12%

Healthcare Company

10%

Media Company

Legal Firm

12%

Financial Services Firm

11%

Comms Service Provider

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	33
Midsize Enterprise	21
Large Enterprise	58

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...

See all answers

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...

See all answers

What needs improvement with Google Cloud Spanner?

See all answers

What do you like most about Microsoft Azure Cosmos DB?

The initial setup is simple and straightforward. You can set up a Cosmos DB in a day, even configuring things like availability zones around the world.

See all answers

What is your experience regarding pricing and costs for Microsoft Azure Cosmos DB?

Microsoft Azure Cosmos DB's pricing model has aligned with my budget expectations because I can tune the RU as I need to, which helps a lot. Microsoft Azure Cosmos DB's dynamic auto-scale or server...

See all answers

What needs improvement with Microsoft Azure Cosmos DB?

I have not utilized Microsoft Azure Cosmos DB multi-model support for handling diverse data types. I'm not in the position to decide if clients will use Microsoft Azure Cosmos DB or any other datab...

See all answers

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Product Reports

Buyer's Guide

Database as a Service (DBaaS)

February 2026

Download Google Cloud Spanner product report

Buyer's Guide

Microsoft Azure Cosmos DB

January 2026

Download Microsoft Azure Cosmos DB product report

Also Known As

Google Spanner

Microsoft Azure DocumentDB, MS Azure Cosmos DB

Overview

Cloud Spanner is the first and only relational database service that is both strongly consistent and horizontally scalable. With Cloud Spanner you enjoy all the traditional benefits of a relational database: ACID transactions, relational schemas (and schema changes without downtime), SQL queries, high performance, and high availability. But unlike any other relational database service, Cloud Spanner scales horizontally, to hundreds or thousands of servers, so it can handle the highest of transactional workloads. With automatic scaling, synchronous data replication, and node redundancy, Cloud Spanner delivers up to 99.999% (five 9s) of availability for your mission critical applications. In fact, Google’s internal Spanner service has been handling millions of queries per second from many Google services for years.

Google

Microsoft Azure Cosmos DB offers scalable, geo-replicated, multi-model support with high performance and low latency. It provides seamless Microsoft service integration, benefiting those needing flexible NoSQL, real-time analytics, and automatic scaling for diverse data types and quick global access.

Azure Cosmos DB is designed to store, manage, and query large volumes of both unstructured and structured data. Its NoSQL capabilities and global distribution are leveraged by organizations to support activities like IoT data management, business intelligence, and backend databases for web and mobile applications. While its robust security measures and availability are strengths, there are areas for improvement such as query complexity, integration with services like Databricks and MongoDB, documentation clarity, and performance issues. Enhancements in real-time analytics, API compatibility, cross-container joins, and indexing capabilities are sought after. Cost management, optimization tools, and better support for local development also require attention, as do improvements in user interface and advanced AI integration.

What are the key features of Azure Cosmos DB?

Scalability: Effortlessly handles scaling for large workloads.
Geo-replication: Provides global data access with low latency.
Multi-model Support: Compatible with diverse data types.
NoSQL Flexibility: Offers a non-relational database experience.
Real-time Analytics: Facilitates data-driven decision-making.
Automation: Simplifies scaling and maintenance processes.

What benefits can users expect from Cosmos DB?

High Performance: Ensures rapid processing and low latency.
Ease of Use: Features a user-friendly interface enhancing deployment speed.
Seamless Integration: Connects effortlessly with Microsoft services.
Security: Offers robust measures to protect data integrity.
Consistent Availability: Ensures continuous access to data worldwide.

Industries use Azure Cosmos DB to support business intelligence and IoT data management, using its capabilities for backend databases in web and mobile applications. The platform's scalability and real-time analytics benefit sectors like finance, healthcare, and retail, where managing diverse datasets efficiently is critical.

Microsoft

Sample Customers

Streak, Optiva, Mixpanel

TomTom, KPMG Australia, Bosch, ASOS, Mercedes Benz, NBA, Zero Friction, Nederlandse Spoorwegen, Kinectify

Buyer's Guide

Google Cloud Spanner vs. Microsoft Azure Cosmos DB

February 2026

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