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    MongoDB Atlas (pay-as-you-go)

    MongoDB Atlas on AWS enables organizations to build intelligent, AI-powered applications that scale effortlessly. As a fully managed NoSQL database and vector search platform, Atlas unifies operational data and search in a single system, helping teams move from prototype to production with enterprise-grade security, high availability, and seamless AWS integrations. Try MongoDB Atlas (Mongo as a Service) today with the free trial tier and get 512 MB of storage at no cost.

    Ratings and reviews

    4.2
    56 ratings
    43%
    50%
    3%
    0%
    4%
    40 AWS reviews
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    16 external reviews
    External reviews are from PeerSpot .

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    Reviews (56)
    Nikhil Thapa

    Cloud database has transformed client demos and supports flexible unstructured data workflows

    Reviewed on Apr 05, 2026
    Review provided by PeerSpot

    What is our primary use case?

    MongoDB Atlas serves as our primary database for storing data. We utilize MongoDB Atlas as our main database solution, which provides us with free space to work with and some MB of free storage. When working with Express.js code as our backend, storing data in JSON format is not required, unlike the problem encountered with SQL. Once we require unstructured data, that is what we use MongoDB Atlas for, and it also frees up some of the memory and storage, so it works very well for our use cases. MongoDB Atlas has free storage that allows us to work with the tools and understand them better. I have highlighted several aspects of this solution.

    How has it helped my organization?

    MongoDB Atlas impacts our organization positively as it is our primary source of working, and we work on multiple client projects to demonstrate at least a demo to them. MongoDB Atlas works very well in our organization. When discussing one of the projects on MongoDB Atlas, the UI is very aesthetically pleasing; we do not have to go and deploy some RDS or other solutions. The cluster is already there; we just have to log in and start working on it. Additionally, there is a simple connection string that allows us to manage security as well. MongoDB Atlas UI facilitates managing security, and there is IP address tracking available, which we can specify. It is separate from others, and I would say the scalability is also very good—the ability to scale the database directly is excellent and does not require server adjustments.

    During my development phase, this is very good and easy to understand, which is beneficial if anyone new comes on board.

    What is most valuable?

    The best feature I would say is that there is free storage, which any NoSQL database provides, such as MongoDB Atlas. Apart from that, there is a very good MongoDB Atlas UI where we can see the cluster, databases, and all these features. When we are using it, the transactions go for real-time processing. These are the features that it offers us, and the connection is very good to any framework we are using in the backend.

    MongoDB Atlas is our primary database, and we prefer this because of the reliability of MongoDB Atlas. The UI is very good for Atlas, and the non-structured database is advantageous because we do not have required schema restrictions. The cluster management and the database handling of Atlas are very good. By using the UI, we can manage this efficiently, and these are the features on MongoDB Atlas that give us what we need.

    What needs improvement?

    I do not find any necessary improvements for MongoDB Atlas; it is already good at handling tasks, and we have a local compass as well. There is no disturbance with MongoDB Atlas; it operates well. The UI is good, although I have checked one aspect in MongoDB Atlas: when we make transactions, they do not process in real-time and require a refresh. I attribute this delay to a minor browser issue, but overall, the compass is already integrated, so I do not see any improvements needed.

    For how long have I used the solution?

    I have been working here for more than three years.

    What do I think about the stability of the solution?

    MongoDB Atlas is stable.

    What do I think about the scalability of the solution?

    MongoDB Atlas scalability is very good.

    How are customer service and support?

    I have not reached out to customer support, as I have not encountered any problems, so I have not needed to contact them.

    Which solution did I use previously and why did I switch?

    I have previously used multiple SQL databases, and I encountered problems in the deployment phase, which often required purchasing services such as RDS or others to deploy SQL databases, leading to additional costs. MongoDB Atlas defines a GUI aspect and database storage advantage.

    How was the initial setup?

    My experience with pricing, setup cost, and licensing is that the pricing is very good, and the setup is very good as well. Licensing for the basic version is free, which is a benefit, although the pricing increases significantly when we use many features. We can also mitigate costs a little by sharing and scaling; these aspects are good in MongoDB Atlas.

    Which other solutions did I evaluate?

    I evaluated other options before choosing MongoDB Atlas, primarily focusing on SQL databases, and I encountered deployment problems with them, particularly regarding the necessity to purchase services for RDS. MongoDB Atlas resolved these issues.

    What other advice do I have?

    I would advise others looking into using MongoDB Atlas to note that it is very cost-efficient, and I suggest trying it ourselves. Whitelisting APIs and IPs is a straightforward process, and these are features of MongoDB Atlas worth exploring. MongoDB Atlas is deployed as its own cloud solution, and there is no SS deployment; it is already clustered within MongoDB Atlas. In our organization, I would say it operates in a private cloud setup. I give this product a review rating of ten out of ten.

    Lintz Veloso

    Developers have benefited from flexibility and performance but pricing has needed further attention

    Reviewed on Nov 04, 2025
    Review provided by PeerSpot

    What is our primary use case?

    I still have recent experience with MongoDB Atlas as I have a contact with a representative for Brazil.

    Azure and OCI are what we use as our main cloud providers.

    I have hands-on experience with OCI, although I don't have a cloud for MongoDB Atlas; I have a cloud for databases and DevOps.

    I don't develop directly with only MongoDB Atlas. However, I know the organization has a license with the product.

    What is most valuable?

    It's a very elastic solution for the purposes of our systems and the developers appreciate it for software development.

    MongoDB Atlas's encryption capabilities help ensure data confidentiality and integrity.

    I believe the software has performed well for us regarding data confidentiality and integrity.

    What needs improvement?

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

    For how long have I used the solution?

    I don't have extensive experience with Linux products since it's not my area in my organization.

    What do I think about the stability of the solution?

    I believe the support is very good because I don't have a problem with the availability of the software.

    What do I think about the scalability of the solution?

    I am aware of the horizontal scaling capability.

    How are customer service and support?

    I would be willing to provide a review for one of the Oracle solutions or other solutions such as Linux as we have a Linux server, X8H56. OCI is the server name I remember, it's OCP.

    Which solution did I use previously and why did I switch?

    Our main cloud provider is Azure, not AWS.

    We have MongoDB Atlas; MongoDB Atlas is what we use.

    How was the initial setup?

    I have tried to use Coherence, but it was a bad experience for us.

    I didn't purchase MongoDB Atlas through AWS Marketplace; I only have a MongoDB Atlas license, not AWS.

    What about the implementation team?

    I have no idea about the pricing or setup cost with MongoDB Atlas.

    What was our ROI?

    I find it easy to use.

    I think it's a good product.

    What's my experience with pricing, setup cost, and licensing?

    I have no idea about the pricing or setup cost with MongoDB Atlas.

    Which other solutions did I evaluate?

    We have MongoDB Atlas; MongoDB Atlas is what we use.

    What other advice do I have?

    I am only familiar with databases and applications. I am from the development team and I am a user of database and cloud but I don't know the infrastructure.

    As a user, I deal with the Oracle Database.

    I know the organization has a license with the product.

    We don't utilize real-time analytics with MongoDB Atlas.

    I don't use MongoDB Atlas directly, so I don't know how it can be improved.

    I would place MongoDB Atlas at a medium level. I would rate it at a six or seven. I believe MongoDB Atlas can improve a little. My overall review rating for this product is six out of ten.

    Dhiraj Verma

    Ensures efficient team collaboration with quick deployment and easy integration

    Reviewed on May 19, 2025
    Review from a verified AWS customer

    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?

    Amazon Web Services (AWS)
    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.

    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.

    Luca Botti

    Supportive features enable effective data management and growth

    Reviewed on Dec 09, 2024
    Review provided by PeerSpot

    What is our primary use case?

    I used MongoDB Atlas for structured data storage as part of an application service provided to one of our customers. The application was based on MongoDB and Atlas. While Google Cloud SQL was used for consulting, I interacted with Google Cloud but was not the final decision maker.

    How has it helped my organization?

    From an operational point of view, there were no costs associated with maintaining the database on my side, and service costs were acceptable from both my side and the customer’s perspective.

    What is most valuable?

    I find MongoDB Atlas highly scalable and easy to use, with very good support. The pricing is quite scalable and applies to various scenarios, both for smaller and bigger companies.

    MongoDB Atlas has supported our data growth well, and my overall impression is very positive. It is easy to work with and has a reliable support structure. For structured data storage and performance, it provides a comprehensive solution, and the feedback was generally positive.

    What needs improvement?

    I am not an expert on what improvements could be made to MongoDB. The service is continually evolving with new features while maintaining reasonable pricing, making it attractive for developers.

    For how long have I used the solution?

    I have been using MongoDB Atlas since 2017 and Google Cloud Platform since 2018.

    What do I think about the stability of the solution?

    There are no issues mentioned regarding stability. I evaluated MongoDB Atlas as not the best solution for the application in the long term, specifically when the services consolidate themselves.

    What do I think about the scalability of the solution?

    MongoDB Atlas scales well and supports data growth effectively.

    How are customer service and support?

    The technical support is very good. I have used them sometimes, even recently, and found the feedback to be spot on our needs.

    What's my experience with pricing, setup cost, and licensing?

    The pricing is quite acceptable and scalable. For our service, it was around 300 to 600 euros per month, which was acceptable for our customers. We could scale up for better performance and scale down when needed.

    What other advice do I have?

    I highly recommend MongoDB Atlas for both smaller and larger companies.

    It is rated an eight out of ten, depending on the use case. As a document-based database, it is one of the better products on the market.

    Dominic

    Amazing product!

    Reviewed on Nov 27, 2024
    Review from a verified AWS customer

    I recently got a chance to to work with MongoDB Atlas on AWS.

    It's a great option to bring these two power houses together and leverage the best of both of them.

    I cannot recommend this product more!

    Bianca

    Powerful and Scalable Database Solution with MongoDB Atlas

    Reviewed on Nov 13, 2024
    Review from a verified AWS customer

    As a developer, I’ve had the opportunity to work with various database solutions, and MongoDB Atlas stands out as one of the best managed database services available today. Here are my thoughts on why I highly recommend MongoDB Atlas, especially for users in the AWS ecosystem:

    - Ease of Use and Quick Setup: Setting up MongoDB Atlas was a breeze. The integration with AWS was seamless, allowing me to deploy clusters in just a few clicks. The user-friendly web interface is intuitive, making it easy to manage databases without a steep learning curve.
    - Scalability and Performance: One of the most impressive features of MongoDB Atlas is its ability to scale effortlessly. Whether you’re dealing with moderate traffic or a sudden spike in user requests, Atlas can automatically adjust resources to ensure optimal performance. The built-in auto-scaling feature is a game-changer for applications that experience fluctuating workloads.
    - Global Distribution and High Availability: With MongoDB Atlas, I can deploy clusters across multiple regions, ensuring low-latency access for users around the globe. The built-in replication and failover mechanisms provide high availability, which is critical for mission-critical applications.
    - Cost-Effective: For a managed service, MongoDB Atlas offers competitive pricing. The pay-as-you-go model allows us to only pay for what we use, making it suitable for startups and large enterprises alike.

    madhura

    Audio embedding resources

    Reviewed on Nov 13, 2024
    Review from a verified AWS customer

    I’d like to suggest adding more resources on using audio embeddings with MongoDB's vector search. Additional guidance on best practices and examples would greatly benefit those looking to work with audio data in MongoDB.

    Sudo

    Powerful and Flexible Database for Gen AI Projects, with Room for Onboarding Improvements

    Reviewed on Nov 13, 2024
    Review from a verified AWS customer

    Creating Mentation, an AI-driven wellness assistant, was an enriching experience, and MongoDB supplied the foundation we required for effortlessly handling intricate and diverse data. By managing user interactions and emotional data as well as processing vector embeddings, MongoDB effortlessly fulfilled our requirements. Its adaptability and scalability proved essential, allowing us to broaden our project’s scope without having to repeatedly reconfigure the database.

    Although the documentation is comprehensive and addresses various use cases, a concentrated, beginner-friendly crash course would have been immensely helpful—particularly for teams such as ours seeking to utilize AWS and Gen AI. Exploring the fundamentals of MongoDB, such as querying, vector indexing, and aggregation pipelines, prompted us to seek out external tutorials, especially to clarify information regarding vector indexing. At one stage, we came across contradictory data from these sources indicating that solely larger M10 clusters were capable of handling vector indexing, which resulted in additional testing and problem-solving.

    Although there were some learning challenges, MongoDB demonstrated to be a robust solution for the requirements of our project. By providing a more efficient onboarding process—centered on key elements and better instructions for utilizing features such as vector indexing—MongoDB would become even more attainable for developers engaged with advanced technology. In general, we had a positive experience with MongoDB, and with some modifications, it could easily become the preferred choice for any developer venturing into Gen AI applications.