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Reviews from AWS customer

36 AWS reviews

External reviews

504 reviews
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4-star reviews ( Show all reviews )

    Dhiraj Verma

Ensures efficient team collaboration with quick deployment and easy integration

  • 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

  • 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


    Luca Botti

Supportive features enable effective data management and growth

  • December 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.

How would you rate customer service and support?

Neutral

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.

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Other


    NIKKI .

Scalable and Highly Flexible NoSQL Database

  • November 26, 2024
  • Review provided by G2

What do you like best about the product?
My favorite feature in this database is the flexibility of its use as well as the possibility to scale it. Because this model stores data in JSON-like formats, it is possible to handle unstructured and semi-structured data without having to prescribe very specific data models. This flexibility is especially good for application where the structure of the data being stored can change as time passes. Being able to scale a database horizontally through the use of sharding is one of MongoDB’s best features since it helps in loading big data and is efficient when dealing with traffic loads. Also, its complex query language; the power offered by the aggregation framework and indexing and data retrieval make the process very efficient and diverse. Moreover, features such as the MongoDB Atlas make cloud deployment and management easy and more enjoyable. MongoDB has gained many supporters of the community and had a great documentation, which makes it fit for today’s developments.
What do you dislike about the product?
Probably one of the biggest negatives of the MongoDB is its steep learning curve for those that have no prior experience with NoSQL systems or have recently migrated from SQL. On the positive side, it is also very flexible, allowing developers to easily create badly thought out schemas, which when the application starts getting a lot of use can slow down the performance immensely. Also, handling shard and replication in self-serving environment quite challenging and may need good understanding of structure. A third anotated limitation is the ACID properties of transactions while MongoDB has added support for these recently and to a far lesser extent than traditional relational database systems, it may not be suitable where high consistency is critical. Finally and as for the offering of MongoDB Atlas, which is a cloud managed service of MongoDB, there is a high likelihood of accumulating high costs particularly for those that are intending to develop jumbo scale applications for their start-ups or small business enterprises.
What problems is the product solving and how is that benefiting you?
It is solving several problems that are inherent in managing huge amount of unstructured or semi structured data. It’s for businesses who are struggling to scale and create flexibility, as well as develop rapidly. Organizations can operate massive datasets and high traffic applications, while performance stays consistent despite the increasing volume of data, thanks to its ability to scale horizontally, or sharding. For businesses with unpredictable or changing data structure, like e-commerce, IoT, social media, this feature is particularly useful.

The biggest benefit for me about MongoDB has to do with being able to modify the data model on the fly without a rigid schema, which helps speed up development due to the iterations necessary. This flexibility allows prototypes of new features to be easier or to simply pivot when business requirements change. Also, MongoDB’s powerful querying and aggregating functionalities make analyzing large dataset very efficient and help in making data driven decision. Also, MongoDB cloud service, MongoDB Atlas, removes my burden of infrastructure management so I can development application and less of database management. From an overall perspective, MongoDB provides for rapid development, scalability, and efficiency that are necessary to compete in the fast changing world.


    madhura

Audio embedding resources

  • November 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

  • November 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.


    Temidayo Kolade

Improvement on Documentation

  • November 12, 2024
  • Review from a verified AWS customer

For my hackathon project, I chose MongoDB Atlas from AWS Marketplace. I particularly like the auto-scaling capability.

However, I encountered some challenges with the SDKs at multiple stages of use, so I had to look outside the official documentation for help. For example, while connecting to the cluster.

While the existing documentation is okay, it would be more beneficial if video resources were included (as this helps better than textual documentation). Additionally, integrating real-world examples and case studies into the documentation could greatly enhance its practical value.


    Anand.

The best solution out there

  • October 22, 2024
  • Review from a verified AWS customer

I've used mongodb professionally for 4 years and have found the product meets and exceeds the demands placed on it by the products i create.


    Atakan Steven B.

Efficient use of NoSQL!

  • August 19, 2024
  • Review provided by G2

What do you like best about the product?
Apart from many other NoSQls on the market, MongoDB also stands out with its speed and efficient indexing method. Also being integrated with MongoDB Compass makes it easy to play around with the data.
What do you dislike about the product?
MongoDB is good for proffesional work but MongoDB Compass interface can be sometimes hard to use.
What problems is the product solving and how is that benefiting you?
As the nature of NoSQL, handling data in our projects, creating schemas are good for our usecases.


    Onkar D.

Connection smoother

  • August 12, 2024
  • Review provided by G2

What do you like best about the product?
Easy to connect
Query understanding is easy
What do you dislike about the product?
lack of query functions as compare to SQL
What problems is the product solving and how is that benefiting you?
No SQL