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.
MongoDB Atlas (pay-as-you-go)
MongoDB, IncExternal reviews
504 reviews
from
and
External reviews are not included in the AWS star rating for the product.
Flexible and Scalable NoSQL Database
What do you like best about the product?
MongoDB’s document-oriented architecture uses JSON-like BSON documents for flexible, schema-less data storage. This allows dynamic adaptation to evolving data structures without rigid schema migrations.
Horizontal scalability via sharding efficiently distributes data across clusters, enabling seamless handling of massive datasets.
The aggregation framework supports complex data transformations, while built-in geospatial indexing and full-text search expand analytical capabilities.
Transaction support (from v4.0) ensures ACID compliance for multi-document operations.
Horizontal scalability via sharding efficiently distributes data across clusters, enabling seamless handling of massive datasets.
The aggregation framework supports complex data transformations, while built-in geospatial indexing and full-text search expand analytical capabilities.
Transaction support (from v4.0) ensures ACID compliance for multi-document operations.
What do you dislike about the product?
The transition from SQL can involve a steep learning curve, particularly for complex queries and aggregation pipelines.
Storage consumption is higher than relational databases due to denormalized data structures, impacting cost efficiency at scale.
While transactions are supported, performance tuning for complex ACID operations requires meticulous indexing and schema design.
Storage consumption is higher than relational databases due to denormalized data structures, impacting cost efficiency at scale.
While transactions are supported, performance tuning for complex ACID operations requires meticulous indexing and schema design.
What problems is the product solving and how is that benefiting you?
MongoDB eliminated rigid schema constraints, allowing our team to rapidly prototype and iterate applications with unstructured data. It streamlined handling high-velocity data streams in IoT projects, avoiding costly schema redesigns during development cycles. The scalability features supported our transition from prototype to production without operational bottlenecks, directly accelerating time-to-market for new features
Ensures efficient team collaboration with quick deployment and easy integration
What is our primary use case?
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?
Best Document No Sql alternative
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
Secure and Familiar Database
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.
Room for improvement in data handling leads to enhanced cost-effective data management performance
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.
Amazing DB
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.
A very good and friendly experience i had with the MongoDB till now.
What do you like best about the product?
Fast data fetching and easy to use and implementaion.
What do you dislike about the product?
Some time we face connective issue with the database. Without any appropriate reason
What problems is the product solving and how is that benefiting you?
Fast data serfing over the internet and easy to manage it even the GUI is really usefull.
MongoDB review
What do you like best about the product?
MongoDB's flexibility and scalability are standout features. Its document-oriented model (using BSON) allows for dynamic, schema-less data structures, making it super versatile for evolving applications. This is especially helpful when dealing with unstructured or semi-structured data.
I also appreciate its horizontal scaling capabilities through sharding, which makes it suitable for handling large datasets and high-throughput applications. Features like indexing, aggregation pipelines, and replica sets for high availability are excellent for both performance and reliability.
For developers, tools like MongoDB Atlas (its cloud platform) simplify deployment and monitoring, saving tons of time.
I also appreciate its horizontal scaling capabilities through sharding, which makes it suitable for handling large datasets and high-throughput applications. Features like indexing, aggregation pipelines, and replica sets for high availability are excellent for both performance and reliability.
For developers, tools like MongoDB Atlas (its cloud platform) simplify deployment and monitoring, saving tons of time.
What do you dislike about the product?
write amplification and potential performance issues under high write loads if not tuned properly. Its flexibility can also be a double-edged sword; having no enforced schema can lead to messy data structures if developers aren't disciplined.
What problems is the product solving and how is that benefiting you?
storing and querying time series data
Supportive features enable effective data management and growth
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
Amazing product!
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!
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