Chroma vs Microsoft Azure Cosmos DB comparison

Chroma and Microsoft are both solutions in the Vector Databases category. Chroma is ranked #10 with an average rating of 8.5, while Microsoft is ranked #1 with an average rating of 8.3. Chroma holds a 8.9% mindshare in VD, compared to Microsoft’s 5.9% mindshare. Additionally, 100% of Chroma users are willing to recommend the solution, compared to 95% of Microsoft users who would recommend it.

Chroma

Read 2 Chroma reviews

4,308 Views
4,308 Comparison Views

100% willing to recommend

Microsoft Azure Cosmos DB

Read 109 Microsoft Azure Cosmos DB reviews

10,499 Views
4,410 Comparison Views

95% willing to recommend

Chroma

Microsoft Azure Cosmos DB

Comparison Buyer's Guide

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Executive SummaryUpdated on Jan 25, 2026

Microsoft Azure Cosmos DB and Chroma are database solutions competing in the scalable and efficient database solutions category for business needs. Chroma's focus on modern analytics capabilities provides a competitive edge for data-intensive applications.

Features: Microsoft Azure Cosmos DB delivers globally distributed, multi-model data handling capabilities with strong consistency options and low latency. Chroma enhances these offerings with sophisticated data modeling capabilities, a strong emphasis on analytics, and advanced AI integration. While Microsoft Azure Cosmos DB sets a standard in comprehensive feature offerings, Chroma's advanced analytical focus appeals to specific data-driven needs.

Ease of Deployment and Customer Service: Microsoft Azure Cosmos DB integrates seamlessly with Microsoft’s cloud ecosystem and provides extensive documentation, allowing businesses already familiar with Microsoft services to experience smoother deployment. Chroma offers a streamlined setup and emphasizes easy integration of analytics features. Both provide strong customer support; however, Microsoft benefits from an expansive cloud infrastructure support network.

Pricing and ROI: Microsoft Azure Cosmos DB is perceived as a high-cost solution, justifying its expense with a robust feature set suitable for large enterprises interested in global reach. In contrast, Chroma is seen as a more cost-effective solution with lower upfront costs, appealing to smaller businesses focused on analytics. Whereas Microsoft Azure Cosmos DB justifies its pricing with comprehensive features, Chroma ensures a significant ROI through specialized data capabilities and reduced initial financial obligations.

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

Buyer's Guide

Chroma 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

Chroma

Ranking in Vector Databases

10th

Average Rating

8.6

Reviews Sentiment

5.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Microsoft Azure Cosmos DB

Ranking in Vector Databases

1st

Average Rating

8.2

Reviews Sentiment

6.9

Number of Reviews

109

Ranking in other categories

Database as a Service (DBaaS) (4th), NoSQL Databases (2nd), Managed NoSQL Databases (1st)

Mindshare comparison

As of February 2026, in the Vector Databases category, the mindshare of Chroma is 8.9%, down from 14.4% compared to the previous year. The mindshare of Microsoft Azure Cosmos DB is 5.9%, up from 1.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Vector Databases Market Share Distribution
Product	Market Share (%)
Microsoft Azure Cosmos DB	5.9%
Chroma	8.9%
Other	85.2%

Vector Databases

Featured Reviews

Sameer Bhangale

Leader, Data Science Practice at a computer software company with 5,001-10,000 employees

Used for RAG (Retrieval-augmented generation) and provides good documentation

If I have to deploy my application in a scalable environment with lots of data and users, I sometimes need to create multiple instances of my database or have a distributed database across different machines. Using Kubernetes, I can quickly increase the horizontal spread of Milvus because it is containerized and readily available. I don't have to do anything by myself. New users can go to Chroma's 'Get Started' page and follow it like a tutorial. Then, they will be ready to use the solution. Chroma has helped us reduce the overall project post production time. Overall, I rate the solution an eight out of ten.

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 solution's most valuable feature is its documentation, which allows new users to easily learn, deploy, and use it."

"It's very easy to set up and runs easily."

"What I appreciate most are the latency and the access, which are guaranteed by the tool, which is really impressive."

"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's most valuable feature is latency."

"The solution is used because we get faster response times with large data sets than with SQL."

"It has been very efficient so far. The team has been using it for quite a while. I am new to the team, but they always talk about how efficient it is."

"It handles large-scale operations efficiently, such as tracking views, logs, or events."

"I would recommend Cosmos. It made our lives a lot easier. There's not a big learning curve in order to understand the structure and how to use it."

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

More Microsoft Azure Cosmos DB pros

Cons

"The hybrid algorithm needs improvement."

"I think Chroma doesn't have a ready-made containerized image available."

"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."

"An improvement could include increasing the document size or providing a method to manage larger sets efficiently. If they want to keep a 2 MB limit, they should provide a way to chain multiple documents in a systematic way so that developers do not have to figure out what to do when a document is larger than 2 MB."

"A couple features that would help me in architectural solutions would be customizable architecture or customizable documentation, which both Microsoft Azure or Microsoft Teams can provide."

"I would give a low rating to Microsoft support, as whenever I talked to them, I never got a solution. I had to guide them."

"One area that could be improved is indexing. Some of the developers struggle with the way the indexing works. We are exploring vector indexing, which we haven't examined fully yet. Indexing is an aspect we're looking to improve upon potentially."

"There is room for improvement in their customer support services."

"They can implement a better backup system or alert system on Microsoft's end. We do receive notices for regular maintenance or updates, but sudden issues create significant problems."

"I have been a devoted Microsoft fan, but Redis DB's memory caching capabilities are really making progress. Even if Cosmos DB is continuously improving and is quite advanced in the field of internal memory optimization, I would still recommend Redis DB to a customer."

More Microsoft Azure Cosmos DB cons

Pricing and Cost Advice

"The current version is an open-source."

"Azure is a pay as you go subscription."

"From a startup point of view, it appears to be expensive. If I were to create my startup, it would not have the pricing appeal compared to the competition, such as Supabase. All those other databases are well-advertised by communities. I know there is a free tier with Azure Cosmos DB. It is just not well advertised."

"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."

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

"Because of the lack of understanding about RUs, the costs become unpredictable. It sometimes goes over the budget."

"Its cost is transparent. Pricing depends on the transaction and data size, but overall, it is cheaper compared to hosting it on your corporate network due to other factors like power consumption."

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

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

More Microsoft Azure Cosmos DB pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

12%

Computer Software Company

11%

Manufacturing Company

10%

University

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	22
Large Enterprise	58

Questions from the Community

What do you like most about Chroma?

The solution's most valuable feature is its documentation, which allows new users to easily learn, deploy, and use it.

See all answers

What needs improvement with Chroma?

The hybrid algorithm needs improvement.

See all answers

What is your primary use case for Chroma?

We collect customer's feedback, and then we present it to the clients.

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

LanceDB vs Chroma

Compared 20% of the time

Supabase Vector vs Chroma

Compared 12% of the time

PostgreSQL vs Chroma

Compared 12% of the time

Redis vs Chroma

Compared 10% of the time

OpenSearch vs Chroma

Compared 9% of the time

More Chroma Competitors

Pinecone vs Microsoft Azure Cosmos DB

Compared 7% of the time

Amazon DynamoDB vs Microsoft Azure Cosmos DB

Compared 7% 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

PostgreSQL vs Microsoft Azure Cosmos DB

Compared 5% of the time

More Microsoft Azure Cosmos DB Competitors

Product Reports

Buyer's Guide

Vector Databases

January 2026

Download Chroma 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

Overview

Chroma is a versatile tool that enhances visual display quality, offering features such as color accuracy improvement, brightness adjustment, and image settings fine-tuning.

It creates vibrant and immersive visual experiences, making it valuable for content creators, gamers, and design professionals.

Chroma's customizable lighting options and seamless integration with other devices are highly praised, allowing users to personalize their setups and create visually stunning effects.

Its compatibility with various devices ensures a cohesive and immersive user experience.

Chroma

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

1. Google 2. Netflix 3. Amazon 4. Facebook 5. Microsoft 6. Apple 7. Twitter 8. Spotify 9. Adobe 10. Uber 11. Airbnb 12. LinkedIn 13. Pinterest 14. Snapchat 15. Dropbox 16. Salesforce 17. IBM 18. Intel 19. Oracle 20. Cisco 21. HP 22. Dell 23. Samsung 24. Sony 25. LG 26. Panasonic 27. Philips 28. Toshiba 29. Nokia 30. Motorola 31. Xiaomi 32. Huawei

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

Buyer's Guide

Chroma vs. Microsoft Azure Cosmos DB

December 2025

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