Cloud database has supported charity platform growth and has improved team delivery speed
What is our primary use case?
MongoDB Atlas is a completely cloud-based database that can be used in real-life applications. I have mostly used it with the MEAN stack, with Angular as a front-end and Node with MongoDB as my primary database in the back-end.
I built a charity-based platform called Danam for orphanages. This platform is currently used by more than 10 orphanages to gain charity from different people, and I implemented MongoDB Atlas there.
What is most valuable?
Setting up MongoDB Atlas is very easy, as I simply select the cluster and the size I want. There are free clusters available for testing real applications, and it is a NoSQL-based database that works well for both web and mobile applications, providing real-time analytics-driven solutions where flexible schema is the main priority.
The best feature MongoDB Atlas offers is the flexible database schema that I can easily set up. It is easy to set up, has no server setup cost, requires no manual setting, and has no downtime. The platform automatically handles traffic spikes and includes built-in features such as storage, auto-scaling, automatic backup, and point-in-time recovery.
Auto-scaling and backups have been instrumental in my project using MongoDB Atlas, especially when I moved from UAT to production. My customer base of more than 10 lakhs increased, and the system automatically scaled to handle those requests, ensuring the database could respond in time.
MongoDB Atlas has an aggregation framework that handles complex analytics without requiring any extra tools. It also provides real-time updates and streaming capabilities.
MongoDB Atlas has positively impacted my organization by reducing operational costs, as I do not need database administrators or server maintenance. It follows a pay-as-you-go strategy, allowing me to increase cluster size by simply paying more, which results in faster development and deployment processes. High availability is also provided through built-in replications and automatic failovers.
My team consists of 18 people, and our uptime has improved to 99.9% and above. The delivery speed has increased, and I have reduced the delivery cycle by 30 to 50 percent.
What needs improvement?
An improvement I can suggest for MongoDB Atlas is achieving even faster query execution and smoother application performance. In terms of scalability, it handles system growth without failure, but it has experienced some outages that could affect uptime.
For how long have I used the solution?
I have been working with this solution for three years.
What's my experience with pricing, setup cost, and licensing?
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 suitable for basic applications. Shared clusters such as M2 or M5 are not costly. I also have access to M10 and M20 for larger usage, and I am currently using M40, which is the latest one.
What other advice do I have?
My advice for others considering MongoDB Atlas is that its scalability is exceptional. Even if you do not currently have schema knowledge, you can still use it. Its performance is quite good, as MongoDB allows you to change your data structure easily and supports fast deployment and development with simple JSON. I rate this product a 10.
Effortless Setup, Powerful Data Handling
What do you like best about the product?
I really appreciate MongoDB's ability to support multiple data structures and document-based storage. The partition tolerance and its high availability make it extremely powerful. The integration and setup with our microservices are super easy, and there is really good documentation available to get started with it. MongoDB Atlas cloud database is extremely great, and we're shifting our focus from on-premise hosting to a cloud-hosted database. Also, it's easy to make changes in the schema because of its document-based modeling.
What do you dislike about the product?
Nothing to dislike about MongoDB. Everything works well with this powerful noSQL database.
What problems is the product solving and how is that benefiting you?
MongoDB solves the problem of saving complex data structures with document-based modeling, making schema changes easy. MongoDB Atlas cloud database is excellent, shifting our focus from on-premise to cloud hosted solutions.
Database with Strong Performance
What do you like best about the product?
MongoDB provides ease and flexibility when working with massive and unstructured data. MongoDB has a document structure that enables the complex data to be stored without schemas. The MongoDB platform scales smoothly and handles both small and big applications. The platform integrates easily with programming languages and environments. It promotes fast development. It offers a scalable and flexible means to manage database operations.
What do you dislike about the product?
The more complex queries will sometimes be less intuitive than what one would find in a traditional SQL database. Certain aspects of the system require further setup or the use of a paying account. Dealing with very large datasets might require a good amount of indexing and optimization. Aggregation pipelines will occasionally be a problem for the new user. It’s a good system, but these small problems occur.
What problems is the product solving and how is that benefiting you?
MongoDB tackles the challenge of handling unstructured and large-scale data with efficiency. It allows for flexible data modeling, fast development, and scaling without hassle. There's built-in replication and sharding for enhanced reliability and performance. All in all, this has saved time, simplified database administration, and supported application development in a scalable fashion.
Effortless Setup, Needs Better Vectorization Support
What do you like best about the product?
I like the basic architecture of MongoDB and how easy it is to find my JSON with Python libraries. It provides a good score with Python libraries, making data export, encryption, and decryption very easy. The latest feature about vector databases is just amazing for me as an AI engineer and has changed the landscape for me. I no longer need to use any other vector database, and I'm really comfortable using MongoDB. The initial setup was very easy, especially with the Mongo Compass and the resources provided for Python, which make it easier than any other setup.
What do you dislike about the product?
The major thing with the record databases is that you need to set them up manually most of the time. I would prefer if there's a setup to define everything from Python code rather than having to go into the Mongo interface and change it there. They don't provide automatic integration of vectorized databases from the Python code, which is a bit of a setback for me.
What problems is the product solving and how is that benefiting you?
I use MongoDB to easily store non-SQL data like JSON objects. It streamlines storing embeddings and integrates well with Python, saving me time and effort. MongoDB's ease of use and vector database feature are game-changers for my AI work.
Perfect for Developers: Flexible Schemas and Powerful Aggregation
What do you like best about the product?
Basically being as a developer i used it for making my schemas for backend in database and it have advantages of bson type structure which helps me to store the values of realtime type data and it helps me to implement aggregation pipeline as well as use the free tier of database of 512 mb which can be used in mongodb compass
What do you dislike about the product?
Nothing everything is fine just vpc connection is quite harder for new person
What problems is the product solving and how is that benefiting you?
Basically we are having chatting software as well as run time key addtion requirement at that time we have implement it for saving the data of different key as well as json type structure and it gives us benefits on pipeline of that schemas as. well
Flexible and scalable documental database system!
What do you like best about the product?
MongoDB is a highly flexible database system that brings several benefits, including support for document nesting and partial indexing across various fields. It continues to allow for robust aggregations, enabling the use of filters and regex operations. At the same time, MongoDB offers a more developer-friendly approach to viewing and modifying any JSON-type documents.
We have choose MongoDB for its inherit flexible and because it scales very well, which is exactly what we need.
What do you dislike about the product?
At times, it can be difficult to determine exactly how much data is being retrieved during an aggregation. Having this information readily available while performing such actions—whether in MongoDB Compass or similar tools—would be a significant advantage for assessing performance concerns and overall efficiency.
What problems is the product solving and how is that benefiting you?
MongoDB serves as the primary database system for our team, handling both the storage and retrieval of business data. We rely on it across all our microservices, organizing different areas of concern by using separate namespaces.
Effortless Document Storage, Steep Learning Curve with C#
What do you like best about the product?
I love how fast and easy it is to spin up a new cluster with MongoDB and store data. The ability to handle unstructured JSON data quickly and provide fast retrieval is incredibly valuable, especially for my AI-based application that utilizes data from web scraping. I find the document store feature of MongoDB particularly beneficial because it allows me to store any type of data without needing to create structures, which simplifies my development process significantly. The simplicity and ease of initial setup in MongoDB make it an ideal first choice for my database needs. Overall, my experience with MongoDB has been very positive, and I am likely to recommend it to others.
What do you dislike about the product?
I find it challenging to learn MongoDB with non-popular tech stacks like C# Dotnet Core Web API. There aren't enough resources available on the internet to facilitate learning how to effectively use MongoDB with Dotnet Core.
What problems is the product solving and how is that benefiting you?
I use MongoDB for fast storage and quick retrieval of unstructured JSON data, which simplifies managing data from my AI-based application without needing predefined structures.
Developers have benefited from flexibility and performance but pricing has needed further attention
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.
How would you rate customer service and support?
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.
Highly flexible and scalable database that can be used as general purpose db
What do you like best about the product?
The flexibility of its schema, and the amount of scalability it provides, be it horizontal or vertical. Aggregation & high availability makes it a wonderful choice. Extremely easy to use and integrate with any language, make it the first choice.
What do you dislike about the product?
Duplicity and no native joins are a concern.
What problems is the product solving and how is that benefiting you?
I had integrated ML features in my application, and SQL based databases, were a nightmare, so I switched over. Now, most of my applications are using mongo.
Easy Solution for data management
What do you like best about the product?
Flexible schema, scalability and high performance ,built in horizontal scaling with sharding (distributes data across multiple servers).
What do you dislike about the product?
When it comes to data consistency compared to SQL, this system by default emphasizes availability and partition tolerance, as described by the CAP theorem. Achieving strong consistency is possible, but it demands careful setup, particularly in configuring write concerns and read preferences.
What problems is the product solving and how is that benefiting you?
Rigid schemas are a hallmark of traditional SQL databases, which require you to define a fixed structure in advance. When your application changes rapidly—such as when you introduce new features or fields—updating the schema can be a cumbersome process. In contrast, MongoDB addresses this issue with its flexible schema approach, allowing you to add or modify fields in your documents without causing downtime.
