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 9.0, while Microsoft is ranked #4 with an average rating of 8.3. Google holds a 6.4% mindshare in DS, compared to Microsoft’s 4.1% 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

1,047 Views
984 Comparison Views

100% willing to recommend

Microsoft Azure Cosmos DB

Read 109 Microsoft Azure Cosmos DB reviews

9,934 Views
1,291 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: December 2025).

Buyer's Guide

Google Cloud Spanner vs. Microsoft Azure Cosmos DB

December 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 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 January 2026, in the Database as a Service (DBaaS) category, the mindshare of Google Cloud Spanner is 6.4%, up from 3.8% compared to the previous year. The mindshare of Microsoft Azure Cosmos DB is 4.1%, up from 0.8% 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	4.1%
Google Cloud Spanner	6.4%
Other	89.5%

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."

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

"It is a very scalable solution."

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

"Google Cloud Spanner is stable."

"The most valuable feature of Azure Cosmos DB is its scalability. That is the biggest reason I use Azure Cosmos DB."

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

"Microsoft Azure Cosmos DB has helped to improve efficiency, providing good response times and allowing the storage of AI process results, which is crucial for feedback loops."

"The most valuable aspect of Cosmos DB is its performance."

"I would rate Microsoft Azure Cosmos DB a ten out of ten."

"Microsoft Azure Cosmos DB offers the response times needed for advanced analytics applications."

"Microsoft Azure Cosmos DB has reduced our total cost of ownership by about half, allowing us to sell our product for about half of what we were selling it before, and Microsoft Azure Cosmos DB is probably 70% of the reason why that's true."

"Cosmos is preferred because of its speed, robustness, and utilization."

More Microsoft Azure Cosmos DB pros

Cons

"The tool needs to improve horizontal scaling."

"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."

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

"The cost can be a bit high."

"The tool lacks to offer AI features."

"To show this in real time, we need a live connection that automatically updates in response to new records being inserted. This automated updating feature is lacking in Microsoft Azure Cosmos DB compared to Databricks."

"The tool's pricing is expensive."

"The one thing that I have been working on with Microsoft with regard to this is the ability to easily split partitions and have it do high-performance cross-partition queries. That is the only place where either our data size or our throughput has grown beyond one partition, so being able to do cross-partition queries efficiently would be my number one request."

"Firstly, having a local development emulator or simulator for Azure Cosmos DB would be beneficial. It would be very handy to have a Docker container that developers can use locally."

"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 operational complexity of Microsoft Azure Cosmos DB can be challenging for individuals who are not tech-savvy."

"One of the most frustrating aspects of Microsoft Azure Cosmos DB right now is that you can only store one vector per document."

"There are no specific areas I believe need improvement as I am happy with what I am getting currently. However, I am open to new features in future versions, like possibly integrating AI features natively into Cosmos DB. Any improvement would be beneficial."

More Microsoft Azure Cosmos DB cons

Pricing and Cost Advice

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

"Google Cloud Spanner is an expensive solution."

"It is expensive."

"The solution is expensive."

"Pricing is mid- to high-end."

"Everything could always be cheaper. I like that Cosmos DB allows us to auto-scale instead of pre-provisioning a certain capacity. It automatically scales to the demand, so we only pay for what we consume."

"Cosmos should be cheaper. We actually intend to stop using it in the near future because the price is too high."

"The Cosmos DB pricing model, initially quite complicated, became clear after consulting with Azure Advisor, allowing us to proceed with confidence."

"Azure is a pay as you go subscription."

"The customer had a high budget, but it turned out to be a little bit cheaper than what they expected. I am not sure how much they have spent so far, but they are satisfied with the pricing."

"The solution is a bit on the expensive side."

"Cosmos DB's pricing structure has significantly improved in recent months, both in terms of its pricing model and how charges are calculated."

More Microsoft Azure Cosmos DB pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

19%

Computer Software Company

13%

Healthcare Company

10%

Media Company

Legal Firm

13%

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...

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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

Comparisons

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Compared 18% of the time

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Compared 15% of the time

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Compared 15% of the time

Amazon RDS vs Google Cloud Spanner

Compared 9% of the time

SingleStore vs Google Cloud Spanner

Compared 6% of the time

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Pinecone vs Microsoft Azure Cosmos DB

Compared 7% of the time

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Amazon DynamoDB vs Microsoft Azure Cosmos DB

Compared 6% of the time

Neo4j Graph Database vs Microsoft Azure Cosmos DB

Compared 6% of the time

MongoDB Enterprise Advanced vs Microsoft Azure Cosmos DB

Compared 6% of the time

More Microsoft Azure Cosmos DB Competitors

Product Reports

Buyer's Guide

Database as a Service (DBaaS)

January 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

December 2025

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