Amazon Timestream vs Microsoft Azure Cosmos DB comparison

Amazon Web Services (AWS) and Microsoft are both solutions in the Managed NoSQL Databases category. Amazon Web Services (AWS) is ranked #6 with an average rating of 9.0, while Microsoft is ranked #1 with an average rating of 8.3. Amazon Web Services (AWS) holds a 6.2% mindshare in MND, compared to Microsoft’s 16.4% mindshare. Additionally, 100% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 95% of Microsoft users who would recommend it.

Amazon Timestream

Read 5 Amazon Timestream reviews

643 Views
643 Comparison Views

100% willing to recommend

Microsoft Azure Cosmos DB

Read 109 Microsoft Azure Cosmos DB reviews

9,934 Views
3,676 Comparison Views

95% willing to recommend

Amazon Timestream

Microsoft Azure Cosmos DB

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Executive SummaryUpdated on Jan 25, 2026

Microsoft Azure Cosmos DB and Amazon Timestream are competing in the data management space. Cosmos DB holds an advantage due to its comprehensive feature set, appealing to diverse applications, while Amazon Timestream excels in time-series data analytics.

Features: Microsoft Azure Cosmos DB provides global distribution, multi-model support, and horizontal scaling, along with a comprehensive set of APIs enabling flexibility and powerful querying capabilities. Amazon Timestream focuses on specialized time-series data capabilities, offering real-time analytics and functions suited for IoT and industrial applications.

Room for Improvement: Microsoft Azure Cosmos DB could improve by offering more cost-effective pricing for small-scale use, enhancing integration with non-Microsoft tools, and simplifying its complex configuration settings. Amazon Timestream might expand to support more diverse data models, increase its scalability for larger datasets, and improve support for more varied industry use-cases beyond IoT and industrial applications.

Ease of Deployment and Customer Service: Microsoft Azure Cosmos DB provides global distribution and comprehensive support options, allowing for solution tailoring as needed. Its streamlined deployment model supports complex, globally distributed solutions. Amazon Timestream focuses on a managed service model with efficient deployment for immediate time-series data needs, emphasizing simplicity and quick setup.

Pricing and ROI: Microsoft Azure Cosmos DB's pricing is based on throughput and storage across regions, potentially leading to higher costs for global scalability but delivering substantial ROI for diverse use cases. Amazon Timestream, with a cost model based on ingested and queried data, offers a cost-effective choice for specific time-series analytics, though its cost efficiency is best realized for time-series functions.

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

Buyer's Guide

Amazon Timestream 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

Amazon Timestream

Ranking in Managed NoSQL Databases

6th

Average Rating

9.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Microsoft Azure Cosmos DB

Ranking in Managed NoSQL 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), Vector Databases (1st)

Mindshare comparison

As of January 2026, in the Managed NoSQL Databases category, the mindshare of Amazon Timestream is 6.2%, down from 10.5% compared to the previous year. The mindshare of Microsoft Azure Cosmos DB is 16.4%, down from 17.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Managed NoSQL Databases Market Share Distribution
Product	Market Share (%)
Microsoft Azure Cosmos DB	16.4%
Amazon Timestream	6.2%
Other	77.4%

Managed NoSQL Databases

Featured Reviews

Sushil Pandey

Data Engineer at Tiger Analytics

It is helpful to get telemetry data from the devices in real-time

It is an easily scalable solution. When it comes to the retention period, if someone wants to change, they have to define it at the start. Later on, if users want to change it again, like, or increase the retention policy, then they have to create the table again and do so, and if it is not done, then we face problems. It will increase the retention, but when you try to insert a record or an older record that is not included in the range of your retention period, then you can face some problems and, like, it will throw some errors. The tool is scalable, but it should be defined at the start as to how much retention you want. For scalability, I rate the tool a six or seven out of ten.

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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.

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 best things about Amazon Timestream are it's maintenance-free, customizable, and has no lag issues. It's always real-time."

"You can quickly aggregate data from the last ten years with Amazon Timestream."

"If you drop a message, the solution's technical support will definitely reply."

"Using Amazon Timestream has been seamless due to its integration within the AWS ecosystem and ease of use for the engineering team."

"What I like best is that the tool is easy to collect and store data and is fast and scalable. The fully managed database is easy to understand."

"The best features of Microsoft Azure Cosmos DB include the speed to query data; as long as you index properly, retrieving data is fast and lightweight."

"The product has a lot of useful features that are there and ready to use, it's also very easy to use."

"The speed is impressive, and integrating our power-up database with Kafka was an improvement."

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

"It is easy to use because you don't need to know much about Cosmos DB or have prior experience."

"Overall, I would rate it a nine out of ten with the only significant issue being the partitioning key functionality."

"Cosmos DB has helped our organization handle large amounts of data."

"The high speed of Azure Cosmos DB compared to other competitors is remarkable."

More Microsoft Azure Cosmos DB pros

Cons

"There are certain features that we would like to see added and we are collaborating with the product teams on these areas."

"Arranging the database schema is a bit challenging."

"The tool could be improved by increasing the batch size from one hundred records to five hundred or a thousand to speed up indexing."

"The solution could be improved by making it easier for new graduates like me to use. Better explanations of queries and how to use them with other AWS services would help."

"There are disadvantages when it comes to time series databases since you can't delete anything from Amazon Timestream data."

"There is room for improvement in terms of stability."

"The integration with other solutions needs to improve because Cosmos DB's interoperability is lacking in some scenarios. For example, I'm currently implementing Fabric. That involves migrating from environments without apps, processing data and users, and taking them to Fabric."

"In the long run, there should be an addition of more features, especially because this space is evolving quickly. It all boils down to how many more features you are adding, how many integrations you are supporting, and how many more APIs you have that are standard APIs."

"It would be nice to have more options to ingest the data, for example, more file options or more search options. Currently, you can use JSON, but if there were other file types you can use for data ingestion, that would be nice."

"The tool's pricing is expensive."

"I do not have any specific suggestions for improvements at the moment. However, having more AI capabilities in the future would be beneficial."

"The query is a little complex. SQL server should have more options. But the query should be better."

"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."

More Microsoft Azure Cosmos DB cons

Pricing and Cost Advice

"Amazon Timestream's pricing seems manageable to me."

"We don't see high costs with Amazon Timestream, which may vary by company."

"We pay over $10 million a year to Amazon."

"For 1GB of data, the solution charges $ 0.01 in the US region."

"Microsoft Azure Cosmos DB is moderately priced, where it is neither expensive nor cheap."

"Cosmos DB is a highly cost-optimized solution when used correctly."

"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."

"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 pricing is not bad. It is good."

"Its price is in the middle, neither too low nor too high."

"Pricing, at times, is not super clear because they use the request unit (RU) model. To manage not just Azure Cosmos DB but what you are receiving for the dollars paid is not easy. It is very abstract. They could do a better job of connecting Azure Cosmos DB with the value or some variation of that."

"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."

More Microsoft Azure Cosmos DB pricing and cost advice

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Top Industries

By visitors reading reviews

Computer Software Company

13%

Manufacturing Company

11%

Insurance Company

Outsourcing 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 experience regarding pricing and costs for Amazon Timestream?

Amazon Timestream's pricing seems manageable to me.

See all answers

What needs improvement with Amazon Timestream?

We are working on a few open change requests with the engineering teams on AWS's side. There are certain features that we would like to see added and we are collaborating with the product teams on ...

See all answers

What is your primary use case for Amazon Timestream?

We use Amazon Timestream as a data historian for IT data. It stores all individual measurements of our customers' IoT devices for a certain period of time, allowing them to perform time-series-base...

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 24% of the time

Amazon DynamoDB vs Amazon Timestream

Compared 16% of the time

Amazon DocumentDB vs Amazon Timestream

Compared 15% of the time

MongoDB Atlas vs Amazon Timestream

Compared 14% of the time

Google Cloud Bigtable vs Amazon Timestream

Compared 8% of the time

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Pinecone vs Microsoft Azure Cosmos DB

Compared 7% of the time

Chroma vs Microsoft Azure Cosmos DB

Compared 7% of the time

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

Managed NoSQL Databases

January 2026

Download Amazon Timestream 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

Amazon Timestream is a fully managed, maintenance-free database offering real-time data handling and seamless long-term data aggregation without merge operations, enhancing scalability and speed for IT environments and IoT data.

This service is customizable and user-friendly, making it a preferred choice for managing time-series data efficiently. Users find it beneficial for real-time analytics, monitoring application health, and automating data pipelines. While data charge management and schema design require attention, active collaboration with AWS is ongoing for feature improvements. Increasing batch size for indexing and simplifying the interface are areas identified for enhancement. The database's scalability is highly appreciated, allowing easy management of data collection and storage.

What are the key features of Amazon Timestream?

Maintenance-Free: Eliminates the need for database maintenance tasks.
Customizable: Offers flexible configurations to fit diverse data needs.
Real-Time Data Handling: Processes data instantly for up-to-the-minute insights.
Seamless Data Aggregation: Efficiently aggregates data over extended periods.
No Merge Operations: Simplifies data updating and management processes.
Scalability: Supports growth with efficient data storage and collection.

Why should users consider Amazon Timestream for their data needs?

Easy Implementation: Simplifies deployment with a user-friendly interface.
Efficient Data Storage: Quickly stores and retrieves large volumes of time-series data.
Enhanced Analytics: Provides tools for in-depth real-time analysis.
Scalable Solutions: Easily adapts to evolving data metrics and usage.
IoT Device Compatibility: Collects and analyzes data from numerous IoT devices.

Industries use Amazon Timestream to manage real-time analytics and application health monitoring. It tracks customer data size, automates pipelines, and supports time-series analyses for scaling. Organizations employ it for telemetry data management, queried in projects like microgrid solar energy, acting as a data historian for storing IoT device measurements.

Amazon Web Services (AWS)

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

Expedia, Intuit, Royal Dutch Shell, Brooks Brothers

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

Buyer's Guide

Amazon Timestream vs. Microsoft Azure Cosmos DB

December 2025

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