Couchbase Capella vs Microsoft Azure Cosmos DB comparison

Couchbase and Microsoft are both solutions in the Database as a Service (DBaaS) category. Couchbase is ranked #15 with an average rating of 7.5, while Microsoft is ranked #4 with an average rating of 8.3. Couchbase holds a 1.4% mindshare in DS, compared to Microsoft’s 4.1% mindshare. Additionally, 100% of Couchbase users are willing to recommend the solution, compared to 95% of Microsoft users who would recommend it.

Couchbase Capella

Read 2 Couchbase Capella reviews

463 Views
245 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

Couchbase Capella

Microsoft Azure Cosmos DB

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Executive SummaryUpdated on Jan 25, 2026

Microsoft Azure Cosmos DB and Couchbase Capella are both competing database solutions offering global distribution and flexible scalability. Microsoft Azure Cosmos DB is more appealing due to its robust support and diverse pricing options, while Couchbase Capella stands out with feature-rich offerings that rate highly in value for cost.

Features: Microsoft Azure Cosmos DB provides automatic scaling, global distribution, and support for multiple APIs, ensuring high versatility. Couchbase Capella offers edge capabilities with in-memory data processing and excellent data synchronization, delivering advantages in workloads benefiting from extensive edge computing capabilities.

Ease of Deployment and Customer Service: Microsoft Azure Cosmos DB integrates seamlessly within the Azure ecosystem, simplifying deployment for users of Microsoft services. It is known for reliable customer support. Couchbase Capella supports straightforward deployment, particularly for hybrid on-premise and cloud environments, with strong support backed by comprehensive documentation, granting flexibility in hybrid setups.

Pricing and ROI: Microsoft Azure Cosmos DB presents a wide range of pricing options offering good ROI, especially for businesses invested in the Azure ecosystem. Couchbase Capella can have higher initial setup costs but demonstrates strong ROI through efficient data handling and feature depth, providing significant long-term benefits. Its cost-effectiveness is justified for those needing specialized capabilities.

To learn more, read our detailed Couchbase Capella vs. Microsoft Azure Cosmos DB Report (Updated: December 2025).

Buyer's Guide

Couchbase Capella 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

Couchbase Capella

Ranking in Database as a Service (DBaaS)

15th

Average Rating

7.6

Reviews Sentiment

7.5

Number of Reviews

Ranking in other categories

AI Data Analysis (18th)

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 Couchbase Capella is 1.4%, up from 0.4% 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%
Couchbase Capella	1.4%
Other	94.5%

Database as a Service (DBaaS)

Featured Reviews

SupriyaKulkarni

Devops Specialist at Amdocs

Good GUI, easy to learn, and simple to install

The architecture is complex. I do understand that. However, the GUI is very user-friendly. Sometimes all these things are a little difficult to understand for a person who is not experienced in Couchbase. There is a constant requirement to upgrade the versions. We need to constantly keep on upgrading the latest version for the newest one. Currently, we are dealing with an issue where some of the servers are on the 6.5 version, and a few have moved to 7.5. So we are in a mixed mode right now. We are having a high IO issue on our servers, which we are already dealing with. We have these cases with Couchbase, with Red Hat, et cetera. We feel like this constant need to upgrade is something that is very mundane yet a very difficult task. If you have three clusters, which have around thirty nodes, the data is quite sensitive. Whenever there is Couchbase upgrade that is going on, we see that our SR is dropped. The purchase rate and success rate drop. This affects our business and the clients. Rebalancing could be improved. I find it to be a very slow process when it comes to rebalancing the clusters. If you talk about other architectures like Oracle, they are pretty fast. Couchbase is a little slower. Rebalancing, taking the node out, doing the upgrade, putting it back, rebalancing it, is a very difficult and cumbersome. For Oracle, we have been running on version 19.5 for the past five years. There were absolutely no issues. Yet for Couchbase, every six months, we have to go do the upgrade.

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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.

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Quotes from Members

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

Pros

"The initial setup was straightforward."

"The way the nodes are managed is interesting."

"The fact that scalability can be achieved by simply configuring availability zones is very attractive."

"It is non-SQL and helps to manage and manipulate data from the coding, rather than direct data and complex queries."

"The most valuable features of Microsoft Azure Cosmos DB include the TTL, the ability to scale up and down as needed, and geo-replication, which comes out of the box."

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

"Microsoft Azure Cosmos DB is very fast."

"Microsoft Azure Cosmos DB is a good solution for distributed application requirements. We can perform multi-modeling."

"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."

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

More Microsoft Azure Cosmos DB pros

Cons

"Rebalancing could be improved."

"The product could be improved by including a log section for tracking activities, enhancing database integration, and providing more transparency regarding pricing and monitoring activities."

"The API compatibility has room for improvement, particularly integration with MongoDB. You have to connect to a specific flavor of MongoDB. We'd also like a richer query capability in line with the latest Mongo features. That is one thing on our wish list. The current version is good enough for our use case, but it could be improved."

"The auto-scaling feature adjusts hourly. We have many processes that write stuff in batches, so we must ensure that the load is spread evenly throughout the hour. It would be much easier if it were done by the minute. I'm looking forward to the vector database search that they are adding. It's a pretty cool new feature."

"The query searching functionality has some complexities and could be more user-friendly. Improvements in this area would be very helpful."

"There were instances where the DB was not responding, and we lost some part of our business due to that."

"One of our biggest pain points is the backup and restore functionality needs improvement. They've gotten a little better in this area. SQL Server's long-term retention is amazing, and you can restore data from years ago. You need to open a support Microsoft ticket to restore your Cosmos DB backup, and it comes in on a different Cosmos account. It's just kind of a headache to restore data."

"In that scenario, two things can be improved."

"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."

"Its stability can be further improved."

More Microsoft Azure Cosmos DB cons

Pricing and Cost Advice

Information not available

"You need to understand exactly the details of how the pricing works technically to stay within reasonable pricing."

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

"The pricing model of Microsoft Azure Cosmos DB is a bit complex."

"Cost isn’t a big hurdle for us right now. The solution is not costly."

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

"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."

"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."

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

More Microsoft Azure Cosmos DB pricing and cost advice

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Top Industries

By visitors reading reviews

No data available

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 needs improvement with Couchbase Capella?

See all answers

What is your primary use case for Couchbase Capella?

The solution is basically used to support our ordering system, which generates a huge number of orders for our customers.

See all answers

What advice do you have for others considering Couchbase Capella?

We are Counchbase customers. Depending on your application, it is good to use Couchbase where you have high OLTP systems where you know there will be constant data loading, deleting, et cetera, hap...

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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Compared 22% of the time

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Compared 17% of the time

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Compared 6% of the time

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Compared 6% of the time

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Compared 6% of the time

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Product Reports

Buyer's Guide

Database as a Service (DBaaS)

January 2026

Download Couchbase Capella product report

Buyer's Guide

Microsoft Azure Cosmos DB

January 2026

Download Microsoft Azure Cosmos DB product report

Also Known As

No data available

Microsoft Azure DocumentDB, MS Azure Cosmos DB

Interactive Demo

Couchbase

Demo not available

Microsoft

Overview

Couchbase Capella is a fully managed NoSQL DBaaS designed for optimal cloud-native performance. It integrates high-speed and flexible JSON applications with real-time analytics, supporting billion-scale vector search.

This platform is tailored for cloud environments, offering enhanced operational efficiency. It supports trusted mobile NoSQL for always-on apps and real-time JSON-native analytics without ETL processes. Couchbase Capella is unique in managing the complete data lifecycle for RAG and agentic systems, providing contextual memory and response validation, facilitating quick and cost-effective development of AI-driven applications.

What are the standout features of Couchbase Capella?

Fully Managed DBaaS: Removes the complexity of database management with automated processes.
Cloud-Native Performance: Optimizes speed and flexibility for internet applications.
JSON Application Support: Facilitates fast and flexible deployment of JSON-based applications.
Billion-Scale Vector Search: Handles extensive data searches efficiently.
Mobile NoSQL Integration: Ensures seamless offline capabilities for mobile apps.
Real-Time Analytics: Provides instant insights without the need for ETL.

What benefits or ROI should you seek in reviews for Couchbase Capella?

Cost-Effectiveness: Offers competitive pricing with high performance.
Operational Efficiency: Minimizes manual database management needs.
Scalability: Easily adapts to growing datasets and application demands.
Flexibility: Supports a variety of use cases with its versatile structure.
Security: Prioritizes data protection and privacy.

In healthcare, Couchbase Capella aids in managing vast amounts of patient data with real-time analytics, ensuring fast application performance for critical decision-making. In retail, it enhances customer experiences through personalized recommendations and dynamic inventory management, while in finance, it supports secure, agile processing of transactions and fraud detection.

Couchbase

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

Information Not Available

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

Buyer's Guide

Couchbase Capella vs. Microsoft Azure Cosmos DB

December 2025

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