MongoDB Atlas Enterprise

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 .

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.

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.

I have been using this product for the past 5 years.

I find the installation process easy to deploy as it wasn't difficult to implement.

The stability of the product is very high, and I would rate it a nine out of ten for stability.

It's very much scalable, and I would rate scalability a nine.

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.

Positive

I personally took part in the installation process.

I can deploy MongoDB Atlas in 2-3 hours.

When we make changes, responsibilities are always distributed. It will be a team whenever a production deployment comes.

My company has seen financial benefits from using MongoDB Atlas through savings because we are using open source.

Postgres is another option that is available for us. I have considered alternatives for MongoDB Atlas.

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.

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.

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.

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.

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.

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

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.

MongoDB Atlas scales well and supports data growth effectively.

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

Neutral

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.

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.

We use an application called Fully Factory in the Indian stock market. It works by setting price ranges for stocks. For example, if the Bank of India stock sells between 800 and 810 rupees, you set a range of 800 to 850 rupees. The system prioritizes buyers with the lowest price and highest quantity.

MongoDB's "find first" function quickly locates and blocks the remote and quantity. The client's amount is shown in the record, and then it's processed. We take around 500 records, and the first 100 are processed in a batch. This gets executed and recorded. Developers handle tasks like JP, AR, and AP separately. We update the client's inventory and pass it to a third party. In Microsoft, we use the same client cover to determine the quantity and product details. This is then executed in their API Acondra server system.

So, MongoDB Atlas is used in stock market applications to handle large-scale data processing.

For security reasons, I prefer MongoDB Atlas. It supports role-based access control, so you have an entity for each individual. 

Spring Cloud ensures I have this set with Atlas, and Spring Security is entering the security for me. That's why I feel Spring Security is much better. Even if you expose a public method, it will be exposed via an authentication token.

If you're putting a direct authentication case authentication with their sync of Google token, just put a sync token directly. It will automatically type your method. Even if you expose a public method, it will be exposed via authentication token. Unmasked analytics, you have PeerSpot on or authentication token. It won't get executed.

It's better to use the predicate in Java side to sort. If you are trying to sort in MongoDB, the comparator of Sandal will be discussed. It can be sorted, but if you can do the competitor in Java, sorting using predicates (filtering conditions) and all, it'll be faster. That is what I noticed. For conditioning sorting in MongoDB might be slower, but I haven't verified that. I am doing sorting using predicate in Java.

Another concern:

When I use RoboMongo with MongoDB, it gets delayed and slower when the records are more than one billion. If the records are more than one billion, the document page will see it's all documents. If you have more than a thousand series in your system, it will be difficult to scroll down and get the reserve the directory. I think if they can have some horizontal way of displaying the reports, they can't be answered, but I'm not sure. The tool is providing protected. However, in RoboMongo, it is tough to see that, of course. It's better at one thousand or four thousand since in a single row.

I have experience with this product. I've used MongoDB intermittently since around 2020. It's a deep system. You need to find the data, and sometimes use queries. There's a conversion tool that helps transform static queries into MongoDB 3 format.

In RDBMS, we have an option to put triggers and functions in the database. In MySQL, you have an option to put a function as well as a trigger, but I haven't found that option in MongoDB. I can create functions, but I am not able to create a function trigger there. We have to create, get, update, and delete, which I can do in MySQL and SQL Server also. But in the same way, you can perform in MongoDB. That is the only thing I noticed. 

Other than that, the query that is performing, creating, updating, and deleting everything can be made possible in MongoDB. You cannot create only that trigger in MongoDB. I haven't found anywhere to create that trigger. 

Without triggers, you can't automatically execute actions in response to data changes in MongoDB.

That is the only drawback that I find with MongoDB: creating the trigger. Apart from that, I think everything can be possible. We can put function software into the database, and you can execute the review. But when creating the triggers, you need to perform separate functions for that. 

Scalability in MongoDB always depends upon the configuration. We can configure it accordingly, but it is definitely essential. 

Your hardware system should also ensure the number of resources your application is consuming. For example, in my application, if the unit is more than 400 kits. In a point of time, it will get executed. 

I tested that using JMeter. When I'm doing the amenity services, I always put the 500 resource at a time. At a single point of time, 500 resources will get in that 5, so I just find any issues on that. The client also has not had any issues.

When we are doing any of the microservices, we need to ensure using JMeter. Via JMeter, you can ensure, like, how much on the port of ten, how much in the source can be accessible.

It's a one-click install. Maybe, like, two settings. If you already have MongoDB, five to ten minutes is regarding some MongoDB. The only thing that you should know is the port number and the IP address if you're exposing your application to a third party. I think if you're aware of those risks, you can install it immediately. It's easy if you need to collect that data. You might know five to ten minutes. 

We can install the remote engineer system. I don't think it will be a bigger task, but even if you're configuring for multiple people, you just need to add that particular port number in your system. Otherwise, it won't allow you to log in.

Even if you're using Microsoft authentication, we normally have multiple layers of authentication. So use the command password, and then you will get the notifications, whether you are getting log-in or not. That will take some time. 

Maintenance:

For getting queries only, we put a Java set. From the development perspective, once the database is set up and you configure the URLs, everything works fine. You have 192.138.1.1 URL, it automatically connects to the review if the network is enabled. Then it connects to the review. However, it definitely depends on the bus service we are passing. It should work fine with no issues if the configuration is okay.

That is how we install it. Once we have source, then it's the same network. If it is on the same network, we have a contract, the traffic is there, and the agent works.

If I want to test whether my microservices work fine, I use them again, and they test if my microservices are working fine. Normally, almost all microservices are in a rack server, so you don't get the performance there. I haven't found any issues directly.

If you are looking for a robust system with a lot of security concerns, then you should go for IBM. I'm not saying MongoDB is not 100% secure, but for highly confidential data, I would suggest other solutions. 

However, in MongoDB, you can do filing processes and vertical reports. Everything can be done in MongoDB, but the newest is a relationship. You cannot maintain the referential integrity relationship. You can maintain it, but it will be a little tough.

If you want to maintain the relational database in MongoDB, the resource should be at least a minimum of one and a half years highly exposed in MongoDB. Then only we'll be able to manage that data. Even for new joiners, it is a little tough to explain how the relational database is maintained in MongoDB. 

Overall, I would rate the solution an eight out of ten. 

The application we are working on is built on MongoDB.

MongoDB is a NoSQL tool. We can easily add fields. It provides more flexibility to store data. It is flexible to changes. I have not encountered any performance issues.

Searching and browsing through the collection must be made easier.

I have been using the solution for two years.

The product has been stable so far.

The installation was easy. The deployment took an hour. One person is enough to deploy the tool. It does not require much maintenance.

I am using the free version of the solution.

I have used DynamoDB before. MongoDB’s free version is quite good for our use cases. DynamoDB is expensive.

MongoDB is a very good tool for first-time users. Overall, I rate the solution an eight out of ten.