Sold by: MongoDB, Inc
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Trusted by global brands, MongoDB Atlas on AWS is a deeply integrated data platform that powers scaled, enterprise level AI applications across various industries.
Overview
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MongoDB Atlas is the data foundation for the AI era, unifying operational, analytical, and AI workloads in a single database platform.
With MongoDB Atlas on AWS, enterprises can turn AI into ROI faster using proven technology, combined industry experience, and dedicated support from MongoDB and AWS.
Try MongoDB Atlas (Mongo as a Service) today with the free trial tier and get 512 MB of storage at no cost. Dedicated clusters start at just USD 0.08 per hour, and you can easily scale up or out to meet the demands of your application. Costs vary based on your specific cluster configurations, network usage, backup policies, and use of additional features. Get started today and see how MongoDB Atlas can help you build and scale your modern applications easily.
Highlights
- MongoDB Atlas integrates native vector search directly into an operational database, significantly simplifying the creation of RAG and agentic AI solutions. This eliminates the necessity for separate search infrastructure, enabling teams to accelerate iteration, optimize dynamically, and expedite the deployment of generative AI applications compared to traditional relational databases.
- MongoDB Atlas has a flexible document model that enables the storage and synchronization of varied data types - structured, unstructured, and semi-structured - even as these datasets change. This makes it an ideal foundation for AI-driven applications that depend on dynamic and diverse information.
- MongoDB Atlas provides robust, built-in security features that safeguard your data and ensure security by default. It complies with key industry standards like HIPAA, GDPR, ISO 27001, and PCI DSS, allowing you to build confidently with industry-leading data protection.
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Deployed on AWS
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Buyer guide
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Pricing
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Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/unit |
|---|---|
MongoDB Atlas Credits used | $1.00 |
Dimensions summary
MongoDB Atlas Credits are a flexible payment mechanism used to pay for services on the MongoDB Atlas cloud platform. One Atlas Credit is equivalent to $1 USD of usage and can be applied toward a wide range of resources, including database clusters, storage, data transfer, backups, and additional Atlas features. There is no upfront charge for Atlas, you simply pay as you consume MongoDB Atlas. This approach enables customers to scale usage based on their needs while maintaining predictable costs, especially when purchased and consumed through the AWS Marketplace.
Top-of-mind questions for buyers like you
How do MongoDB Atlas Credits work for billing purposes?
MongoDB Atlas Credits act as a flexible currency within the Atlas platform, where 1 credit equals $1 USD. With no upfront charges, customers only pay for what they use, credits are automatically deducted based on actual consumption of resources like database instances, storage, and features via AWS Marketplace.
What factors determine my MongoDB Atlas usage costs?
MongoDB Atlas usage costs are determined by factors like cluster tier, cloud provider, storage, IOPS, backup size, data transfer, and add-on features such as Atlas Search. You pay per hour or per operation, with no upfront charges, allowing scalable, flexible billing based on actual resource consumption and usage patterns.
Can I estimate my MongoDB Atlas costs before committing to a purchase?
MongoDB provides a pricing calculator on their website to estimate costs based on your expected workload and configuration needs. Additionally, you can start with a free tier to test the service, and Atlas offers real-time usage monitoring to help track and forecast your credit consumption.
Vendor refund policy
This is a pay as you go service. You will be invoiced based on your usage.
Custom pricing options
Request a private offer to receive a custom quote.
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Delivery details
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Updated weekly
By MongoDB, Inc
By SingleStore
Top
10
In Databases & Analytics Platforms, Generative AI
Top
10
In Data Analysis, Databases & Analytics Platforms, Databases
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10
In Analytic Platforms, Databases & Analytics Platforms, Databases
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
Vector Search Capability
Native vector search integration directly within the operational database, enabling efficient RAG and agentic AI solution development
Data Model Flexibility
Document-based model supporting storage and synchronization of structured, unstructured, and semi-structured data types with dynamic adaptability
Security Compliance
Built-in security features compliant with industry standards including HIPAA, GDPR, ISO 27001, and PCI DSS
Database Workload Unification
Single platform supporting operational, analytical, and AI workloads simultaneously
AI Application Infrastructure
Advanced data foundation designed specifically for powering enterprise-level AI applications across multiple industries
Database Architecture
Multi-purpose database supporting key-value, JSON documents, SQL query, vectors, and full-text search capabilities
Scalability Model
Dynamic scaling with ability to scale out, in, up, and down across individual database services
Data Synchronization
Fully managed data synchronization for mobile and IoT use cases with edge device support
Security Framework
Advanced role-based access control (RBAC) with encryption for data in transit and at rest
Analytics Processing
Native JSON-based analytics with zero ETL transformation and real-time processing architecture
Distributed Database Architecture
Fully managed, distributed SQL database supporting transactional and analytical workloads in a single engine
Vector Search Capabilities
Integrated vector search functionality with indexed search for AI applications and generative AI use cases
High-Performance Data Ingestion
Ability to ingest millions of events per second using parallel, distributed lock-free pipelines
Concurrent Query Processing
Supports scaling access to tens or hundreds of thousands of concurrent users with super-low latency queries
Cloud-Native Infrastructure
Built on a modern, lock-free cloud-native architecture enabling elastic scalability and high-performance data processing
Validated by AWS Marketplace
FedRAMP
GDPR
HIPAA
ISO/IEC 27001
PCI DSS
SOC 2 Type 2
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No security profile
Standard contract
No
No
Customer reviews
4.2
36 ratings
36 AWS reviews
|
503 external reviews
Star ratings include only reviews from verified AWS customers. External reviews can also include a star rating, but star ratings from external reviews are not averaged in with the AWS customer star ratings.
Dhiraj Verma
Ensures efficient team collaboration with quick deployment and easy integration
Reviewed on May 19, 2025
Review provided by PeerSpot
What is our primary use case?
We are using MongoDB Atlas for our log storage, transactional log storage, and we are into CPaaS business, communication platform as a service.
We are also using PostgresSQL in some of the applications, alongside MongoDB Atlas .
What is most valuable?
The most valuable features of MongoDB Atlas in handling large data volumes include collection size and its NoSQL database capabilities.
The security features of MongoDB Atlas support our organization very well.
My company has seen financial benefits from using MongoDB Atlas because we are using open source.
What needs improvement?
There is nothing about MongoDB Atlas I would like to improve or any weak points at this time.
I have not thought through what other features I would like to see included in future updates.
MongoDB Atlas should support containerization.
For how long have I used the solution?
I have been using this product for the past 5 years.
What was my experience with deployment of the solution?
I find the installation process easy to deploy as it wasn't difficult to implement.
What do I think about the stability of the solution?
The stability of the product is very high, and I would rate it a nine out of ten for stability.
What do I think about the scalability of the solution?
It's very much scalable, and I would rate scalability a nine.
How are customer service and support?
For premium support, I would rate the support of MongoDB Atlas a nine.
Premium support requires additional payment; otherwise, you can manage whatever you can yourself.
Though I am currently not using support, I would rate it a nine.
How would you rate customer service and support?
Positive
How was the initial setup?
I personally took part in the installation process.
I can deploy MongoDB Atlas in 2-3 hours.
What about the implementation team?
When we make changes, responsibilities are always distributed. It will be a team whenever a production deployment comes.
What was our ROI?
My company has seen financial benefits from using MongoDB Atlas through savings because we are using open source.
Which other solutions did I evaluate?
Postgres is another option that is available for us. I have considered alternatives for MongoDB Atlas.
What other advice do I have?
The database team consists of five to six people.
We are not currently using the AI functionality in MongoDB Atlas, though AI-driven projects are available in their vector search.
Based on my experience, I would recommend MongoDB Atlas to other users looking for NoSQL databases.
We do everything on our own and are not using third-party services for maintenance.
I am involved in the maintenance process.
We are using MongoDB Atlas for commercial purposes.
The number of people currently using this product in my organization is related to my platform hosted on MongoDB Atlas.
I think it's a competitive solution compared to others, though I cannot comment on pricing as I haven't seen pricing for other products.
I rate MongoDB Atlas a nine out of ten.
Which deployment model are you using for this solution?
On-premises
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
אייל .
Best Document No Sql alternative
Reviewed on May 09, 2025
Review provided by G2
What do you like best about the product?
Ease of use, Ease of implementation, Ease of integration, and a lot of documentation online.
What do you dislike about the product?
Cluster reliability, database error protection, data consistency
What problems is the product solving and how is that benefiting you?
Database for a transactional payments system
Fenil S.
Secure and Familiar Database
Reviewed on May 06, 2025
Review provided by G2
What do you like best about the product?
MongoDB excels with its flexible document model, which allows for dynamic schema design—making it perfect for fast-paced development cycles and agile teams. Its JSON-like BSON storage format aligns well with modern JavaScript-based stacks like MERN, ensuring smooth data handling from front end to backend. The built-in horizontal scaling, support for geospatial queries, and full-text search are game-changers in terms of versatility.
What do you dislike about the product?
While MongoDB is powerful, it does have some drawbacks. It can consume significantly more storage than traditional relational databases due to its denormalized document structure. For applications with complex relationships, performance tuning requires careful indexing and schema design.
What problems is the product solving and how is that benefiting you?
MongoDB helps us handle flexible and fast-changing data without worrying about strict schemas. It’s great for building apps quickly, especially when data structures vary. We’ve saved time and avoided complex migrations, and with MongoDB Atlas, scaling and managing the database is super simple.
Laksiri Bala
Room for improvement in data handling leads to enhanced cost-effective data management performance
Reviewed on Mar 26, 2025
Review provided by PeerSpot
What is our primary use case?
I primarily use Oracle databases, but I work with many other databases such as MongoDB Atlas and several cloud databases. I utilize MongoDB Atlas predominantly for training-level projects in resource grooming and for sub-projects at my office. It is used alongside Oracle and Postgres in these training layers.
What is most valuable?
MongoDB Atlas offers replication, which is cheaper than Oracle RAC, making it appealing to certain industries. It is particularly useful for unstructured and semi-structured data because of its performance in these areas. Sharding and partitioning are supported, though they don't reach the same level as Oracle's capabilities. This cost-effective solution assists organizations in data storage and management.
What needs improvement?
It would be beneficial if MongoDB Atlas could better support OLTP aspects and data frames, as well as enhance its capabilities for data pipelines and visualization dashboards. Furthermore, supporting the medallion architecture could be a valuable addition, and incorporating improved spatial and vector handling for geographical data could make it more competitive. Enhancing vector processing for AI capabilities would also be critical.
What do I think about the stability of the solution?
MongoDB Atlas is effective for unstructured and semi-structured data, but when it comes to OLTP transactions, its performance declines. This is a continuous challenge I face when utilizing MongoDB Atlas.
What do I think about the scalability of the solution?
MongoDB Atlas offers sharding as a scalability feature, although it does not perform as well as Oracle. Partitioning is also available; however, it lacks a multi-tenancy architecture, which affects its scalability in comparison.
How are customer service and support?
Technical support from MongoDB Atlas, which is open source, is satisfactory in most cases. However, when compared to top databases like EDB, Postgres, and Oracle, the features of MongoDB Atlas fall short, resulting in an average rating due to higher-expectation features still lacking in its offerings.
How would you rate customer service and support?
What's my experience with pricing, setup cost, and licensing?
The price of MongoDB Atlas is reasonable, which is why many organizations, including mine, are opting for it.
What other advice do I have?
The overall rating for MongoDB Atlas is around 5.5. To improve, MongoDB should enhance support for demanding graph databases, vector databases, and spatial handling. Additionally, improvements in AI capabilities, particularly vector processing, are imperative. These developments could provide MongoDB Atlas with a competitive edge.
Mon
Amazing DB
Reviewed on Feb 05, 2025
Review from a verified AWS customer
I recently had the opportunity to work with MongoDB Atlas on AWS, and I must say, the experience has been nothing short of impressive. Bringing together the power of MongoDB's flexible, scalable NoSQL database with the robust infrastructure and services of AWS creates a seamless, high-performance environment for managing data-intensive applications.
Performance optimization is another key advantage. With features like auto-scaling, performance monitoring, and workload isolation, MongoDB Atlas on AWS eliminates much of the operational overhead, allowing developers to focus on building applications rather than managing infrastructure. Additionally, the automated backups and failover mechanisms provide peace of mind, ensuring that critical data is always protected.