Amazon Timestream vs MongoDB Atlas comparison

Amazon Web Services (AWS) and MongoDB are both solutions in the Managed NoSQL Databases category. Amazon Web Services (AWS) is ranked #7 with an average rating of 9.0, while MongoDB is ranked #3 with an average rating of 8.2. Amazon Web Services (AWS) holds a 5.0% mindshare in MND, compared to MongoDB’s 14.4% mindshare. Additionally, 100% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 96% of MongoDB users who would recommend it.

Amazon Timestream

Read 5 Amazon Timestream reviews

973 Views
973 Comparison Views

100% willing to recommend

MongoDB Atlas

Read 52 MongoDB Atlas reviews

10,036 Views
2,509 Comparison Views

96% willing to recommend

Amazon Timestream

MongoDB Atlas

Comparison Buyer's Guide

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Executive SummaryUpdated on Jan 11, 2026

MongoDB Atlas and Amazon Timestream compete in the database solutions category, with MongoDB Atlas having the upper hand in general-purpose applications due to its flexibility, while Amazon Timestream excels in specialized time-series management.

Features: MongoDB Atlas provides autoscaling, a flexible schema, and cross-platform abilities, allowing easy integration and scalability across different zones. Amazon Timestream offers maintenance-free operation, seamless AWS integration, and efficient time-series querying capabilities, making it ideal for real-time applications and data aggregation over long periods.

Room for Improvement: MongoDB Atlas could enhance its time-series data handling, reduce complexity for less experienced users, and improve cost management for large deployments. Amazon Timestream may benefit from broader integration capabilities outside AWS, more flexible deployment options, and enhanced querying language support for complex data sets.

Ease of Deployment and Customer Service: MongoDB Atlas facilitates deployment with its cloud-native architecture and cross-cloud provider support, offering robust customer service. Amazon Timestream benefits from being integrated into the AWS ecosystem, providing a smooth deployment process and strong support within the AWS infrastructure, yet it may restrict users to AWS-related environments.

Pricing and ROI: MongoDB Atlas uses a pay-as-you-go model suitable for dynamic workloads, potentially leading to significant savings for startups but higher costs for extensive use cases. Amazon Timestream offers competitive pricing for AWS-oriented businesses, providing cost efficiency through its tailored pricing for time-series applications, directly enhancing ROI for companies deeply invested in AWS.

To learn more, read our detailed Amazon Timestream vs. MongoDB Atlas Report (Updated: June 2026).

Buyer's Guide

Amazon Timestream vs. MongoDB Atlas

June 2026

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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

7th

Average Rating

9.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

MongoDB Atlas

Ranking in Managed NoSQL Databases

3rd

Average Rating

8.4

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Database as a Service (DBaaS) (3rd), Database Management Systems (DBMS) (2nd), AI Software Development (4th)

Mindshare comparison

As of June 2026, in the Managed NoSQL Databases category, the mindshare of Amazon Timestream is 5.0%, down from 8.6% compared to the previous year. The mindshare of MongoDB Atlas is 14.4%, up from 6.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Managed NoSQL Databases Mindshare Distribution
Product	Mindshare (%)
MongoDB Atlas	14.4%
Amazon Timestream	5.0%
Other	80.6%

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.

Read full review

Varuns Ug

Senior Software Developer at NIT

Flexible document workflows have accelerated schema changes and simplified evolving data models

MongoDB Atlas currently has almost all the features we require, but there are some points where I see certain improvements. One area is cost visibility and optimization. Since pricing is largely based on storage and cluster size, it can sometimes be difficult to predict or optimize cost without deeper insights. More granular cost breakdowns or recommendations would be helpful. Another area I can mention is performance tuning transparency. While MongoDB Atlas provides monitoring and suggestions, debugging deeper issues like slow queries, index efficiency, or shard imbalance can sometimes require more control or visibility. Cost optimization, deeper performance insight, and easier scaling decisions would make MongoDB Atlas even more powerful. A couple of additional areas where MongoDB Atlas could improve are integrations and developer experience. For integrations, while MongoDB Atlas supports major cloud providers and tools, deeper and more seamless integration with observability patterns would make troubleshooting distributed systems easier. On the documentation side, while it is generally good, some advanced topics like sharding strategies, performance tuning, and real-world scaling patterns could benefit from more practical guidance. Additionally, a better local-to-cloud development experience, making it easier to replicate production-like MongoDB Atlas environments locally, would help developers test performance and scaling scenarios more efficiently.

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."

"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."

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

"The auto-scaling feature is the most valuable aspect."

"MongoDB Atlas is a platform as a service and it has proven to be particularly valuable due to its self-managing nature. This has allowed us to minimize the amount of time and effort required to manage it, as it effectively manages itself. Additionally, it is a complete solution when looking at its features."

"I am impressed with the tool's integrations."

"I would recommend MongoDB Atlas for those who want to start using it."

"The integration and configuration of this product in our AWS environment were easy and straightforward."

"It can store data as a flat file, similar to a file system."

"This solution is very helpful due to its ease of use."

"It is a solid product, very sustainable, and it takes minimal effort to solve a problem while being very easy to deploy."

More MongoDB Atlas pros

Cons

"Arranging the database schema is a bit challenging."

"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."

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

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

"Searching and browsing through the collection must be made easier."

"Customer support needs improvement knowledge-wise."

"An area for improvement in MongoDB Atlas is that it does not support individual or personal database backup, though it supports cloud cluster backup."

"The replica side, like the venue, can be improved."

"The solution is expensive overall."

"I would say pricing is an area where MongoDB Atlas could improve."

"MongoDB Atlas currently has almost all the features we require, but there are some points where I see certain improvements."

"We had some edge cases where scalability was an issue where a node went offline, and we had to deal with that."

More MongoDB Atlas cons

Pricing and Cost Advice

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

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

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

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

"In my previous company, the product allowed use to build a database in a highly regulated environment with the ability to get distributed storage. We used MongoDB as a distributed storage to set up this environment for a critical business application with millions of dollars."

"The tool is free since it's an open-source product."

"The solution is fairly priced. I rate the pricing a seven out of ten."

"The price of MongoDB Atlas is highly affordable."

"For me, MongoDB is expensive, but I think it is not so expensive for customers."

"MongoDB Atlas is not expensive, and since it's a cloud-based solution, you pay by usage."

"We pay for a license."

"We're currently using the Atlas for the night and don't require a license. However, it can be a problem if you want to use their enterprise environment. Then you need to purchase the license."

More MongoDB Atlas pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

14%

Computer Software Company

12%

Manufacturing Company

11%

Outsourcing Company

Manufacturing Company

14%

Financial Services Firm

12%

Construction Company

10%

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	24
Midsize Enterprise	11
Large Enterprise	23

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...

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What is your experience regarding pricing and costs for MongoDB Atlas?

Pricing-wise, MongoDB Atlas has a pay-as-you-go strategy. The documentation for MongoDB is very good; I have learned multiple things through reading it. The free tier is M0 for $0, which is suitabl...

See all answers

What needs improvement with MongoDB Atlas?

See all answers

What is your primary use case for MongoDB Atlas?

In my day-to-day work, I use MongoDB Atlas primarily for storing and querying semi-structured or dynamic data where schema flexibility is important, as I work extensively on schema design, indexing...

See all answers

Comparisons

Amazon DynamoDB vs Amazon Timestream

Compared 19% of the time

MongoDB Enterprise Advanced vs Amazon Timestream

Compared 18% of the time

Microsoft Azure Cosmos DB vs Amazon Timestream

Compared 14% of the time

Amazon DocumentDB vs Amazon Timestream

Compared 13% of the time

Amazon Neptune vs Amazon Timestream

Compared 8% of the time

More Amazon Timestream Competitors

Amazon RDS vs MongoDB Atlas

Compared 8% of the time

Microsoft Azure Cosmos DB vs MongoDB Atlas

Compared 7% of the time

MongoDB Enterprise Advanced vs MongoDB Atlas

Compared 6% of the time

Google Cloud SQL vs MongoDB Atlas

Compared 6% of the time

Microsoft Azure SQL Database vs MongoDB Atlas

Compared 5% of the time

More MongoDB Atlas Competitors

Product Reports

Buyer's Guide

Managed NoSQL Databases

May 2026

Download Amazon Timestream product report

Buyer's Guide

MongoDB Atlas

June 2026

Download MongoDB Atlas product report

Also Known As

No data available

Atlas, MongoDB Atlas (pay-as-you-go)

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)

MongoDB Atlas stands out with its schemaless architecture, scalability, and user-friendly design. It simplifies data management with automatic scaling and seamless integration, providing dynamic solutions for diverse industries.

MongoDB Atlas offers a cloud-based platform valued for its seamless integration capabilities and high-performance data visualization. It features advanced security options such as encryption and role-based access control alongside flexible data storage and efficient indexing. Users benefit from its robust API support and the ability to manage the platform without an extensive setup process. Feedback suggests improvements are needed in usability, query performance, security options, and third-party tool compatibility. While pricing and support services could be more economical, there is a demand for enhanced real-time monitoring and comprehensive dashboards, as well as advanced containerization and scalability options supporting complex database structures.

What are the key features of MongoDB Atlas?

Schemaless Architecture: Flexible data storage without predefined structure.
Automatic Scaling: Dynamically adjusts resources to meet demand.
Advanced Security: Encryption and role-based access control.
User-Friendly Interface: Simplified management and operation.
Robust API Support: Facilitates integration with applications.

What benefits should you consider in a solution like MongoDB Atlas?

Cost-Effective Management: Minimizes setup and operational costs.
Dynamic Data Management: Adapts to varying business demands.
Seamless Integration: Connects easily with other tools and frameworks.
High Performance: Optimized for real-time data processing and visualization.
Reliable Support: Accessible assistance and comprehensive documentation.

In healthcare and finance, MongoDB Atlas manages payment transactions and facilitates real-time analytics, powering SaaS solutions and storing large volumes of user data. It enhances scalability, performance, and security for cloud hosting, IoT integrations, and Node.js environments, widely favored for its flexibility and capability to support microservices.

MongoDB

Sample Customers

Expedia, Intuit, Royal Dutch Shell, Brooks Brothers

Wells Fargo, Forbes, Ulta Beauty, Bosch, Sanoma, Current (a Digital Bank), ASAP Log, SBB, Zebra Technologies, Radial, Kovai, Eni, Accuhit, Cognigy, and Payload.

Buyer's Guide

Amazon Timestream vs. MongoDB Atlas

June 2026

Free Report: Amazon Timestream vs. MongoDB Atlas

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