Google Cloud Spanner vs Microsoft Azure Cosmos DB comparison

Google Cloud Spanner vs. Microsoft Azure Cosmos DB

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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 March 2026, in the Database as a Service (DBaaS) category, the mindshare of Google Cloud Spanner is 7.8%, up from 4.1% compared to the previous year. The mindshare of Microsoft Azure Cosmos DB is 4.4%, up from 1.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Database as a Service (DBaaS) Mindshare Distribution
Product	Mindshare (%)
Microsoft Azure Cosmos DB	4.4%
Google Cloud Spanner	7.8%
Other	87.8%

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

"It is a very scalable solution."

"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."

"Google Cloud Spanner is stable."

"Big data, along with data analysis, is one of the valuable features."

"Microsoft Azure Cosmos DB is very easy to use."

"The best part of Microsoft Azure Cosmos DB is that with the default configuration and the Azure functional pipeline, if your go-to cloud provider is Microsoft Azure, the whole integration is seamless."

"Microsoft Azure Cosmos DB's most valuable feature is latency."

"Specifically, we are using the MongoDB API, so we leverage it in that way. I like the flexibility that it offers. My team does not have to spend time building out database tables. We can get going fairly quickly with being able to read and write data into a MongoDB collection that is hosted inside Azure Cosmos DB."

"I like the scalability, there aren't any constraints for posting in the geolocation, and I also like the SQL architecture."

"It is integral to our business because it helps manage schema and metadata for all our documents and customers. The AI insights we glean based on Azure OpenAI also end up in Cosmos DB. We need a NoSQL store because the schema is dynamic and flexible, so Cosmos DB is a great fit. It has four nines or possibly five nines availability, excellent geo-distribution, and auto-scaling."

"It is one of the simpler databases to work with in terms of code management, tracking, and debugging due to its straightforward data storage and retrieval mechanisms."

More Microsoft Azure Cosmos DB pros

Cons

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

"The tool needs to improve horizontal scaling."

"The cost can be a bit high."

"The tool lacks to offer AI features."

"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."

"Better documentation on how to integrate with other components would be helpful because I was struggling with this."

"The cost can sometimes be high, especially during cross-partition queries with large data amounts."

"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."

"Microsoft Azure Cosmos DB's pricing model is complicated, which people don't understand."

"There are multiple approaches to implementing multitenant architecture on Azure Cosmos DB, but there is still no single or best-recommended approach when you have a big variance in the size of your tenants. That is something that still needs to be worked on."

"We are at the beginning of production, and everything is working very well. The price can always be lower, but currently, it's not a problem."

"The current data analytics of Cosmos DB is inefficient for large-scale queries due to its transactional design."

"We had some performance issues with a data segregation query. We worked closely with Microsoft to solve the problem of performance where, for example, one query had a delay of almost two or three minutes for this one use case. Microsoft tried to improve the product, but in the end, the solution was to change to MongoDB. MongoDB had better performance."

More Microsoft Azure Cosmos DB cons

Pricing and Cost Advice

"Google Cloud Spanner is an expensive solution."

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

"The solution is expensive."

"It is expensive."

"If you are a small organization or startup building from scratch without the Microsoft Startup Founder Club support, it could be expensive."

"Cosmos DB is cost-effective when starting but requires careful management."

"Cosmos DB gave us three accounts for $400. We pay according to the usage."

"Azure Cosmos DB is generally a costly resource compared to other Azure resources. It comes with a high cost. We have reserved one thousand RUs. Free usage is also limited."

"The pricing is perceived as being on the higher side. However, if you have large data operations, it might reduce costs due to performance efficiencies."

"It seems to have helped significantly. We were using a different database system previously, and one of the reasons for acquiring Microsoft Azure Cosmos DB was cost."

"I would rate Cosmos DB's cost at seven out of ten, with ten being the highest."

"For the cloud, we don't pay for the license, but for the on-prem versions, we do pay."

More Microsoft Azure Cosmos DB pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

23%

Computer Software Company

12%

Healthcare Company

Media Company

Legal Firm

12%

Financial Services Firm

10%

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	22
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...

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 needs improvement with Google Cloud Spanner?

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.

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...

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...

Oracle Database as a Service vs Google Cloud Spanner

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Compared 16% of the time

MongoDB Atlas vs Google Cloud Spanner

Compared 13% of the time

Yugabyte Cloud vs Google Cloud Spanner

Compared 11% of the time

Amazon RDS vs Google Cloud Spanner

Compared 6% of the time

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Pinecone vs Microsoft Azure Cosmos DB

Compared 6% of the time

Amazon DynamoDB vs Microsoft Azure Cosmos DB

Compared 6% of the time

MongoDB Atlas vs Microsoft Azure Cosmos DB

Compared 5% of the time

MongoDB Enterprise Advanced vs Microsoft Azure Cosmos DB

Compared 5% of the time

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Product Reports

Database as a Service (DBaaS)

Download Google Cloud Spanner product report

Microsoft Azure Cosmos DB

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

Google Cloud Spanner vs. Microsoft Azure Cosmos DB