MongoDB - A highly scalable NoSQL Database Solution
What do you like best about the product?
MongoDB is the leading NoSQL database solution. It provides a high schema flexibility as MongoDB’s document-based structure allows for a highly flexible schema design.
One of the key features of MongoDB is it supports horizontal scaling through sharding, which allows data to be distributed across multiple servers. This is the reason for its high scalability. It is also cross-platform compatible and has a large and active community, providing a wealth of resources, tutorials, and forums.
What do you dislike about the product?
For users transitioning from relational databases, MongoDB’s lack of native SQL support can be a drawback. It may require additional learning.
What problems is the product solving and how is that benefiting you?
During my internship at Advit RealInfo, we were working on building a CMS for the organization. We ended up utilizing MongoDB since MongoDB’s flexible schema is ideal for content management systems where the structure of stored data can vary widely. It allows for easy storage and retrieval of diverse content types such as the document-based financial data we were working with, without strict schema definitions.
Offers other benefits like high performance, document-oriented storage, and flexibility in data modeling
What is our primary use case?
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.
What is most valuable?
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.
What needs improvement?
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.
For how long have I used the solution?
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.
What do I think about the stability of the solution?
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.
What do I think about the scalability of the solution?
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.
How was the initial setup?
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.
What other advice do I have?
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.
Reviewing MongoDb
What do you like best about the product?
MongoDb Atlas free hosting platform to start with project is the best. It's simplicity to connect with project makes it easy to use with different backend languages.
What do you dislike about the product?
Didn't found as such, overall it's good.
What problems is the product solving and how is that benefiting you?
I personally use mongoDb in most of my full stack application. Using MongoDb, atleast my hosted application I could show off during interviews.
MongoDB best NoSql dabase management system
What do you like best about the product?
What i like most about MongoDB is that it is very easy to use, when i worked with React and required to retrieve or store data i integrated MongoDB with Nodejs.It has document based schema which makes it look much easier.
What do you dislike about the product?
It does not support ACID properties. And it slows down when inconsistent or unbalanced data is shared.
What problems is the product solving and how is that benefiting you?
To handle data for applications which requires to store and retrieve data easily and faster, MongoDB is the best Database management system for such applications .
Using MongoDB: Leveraging Capabilities While Handling Obstacles
What do you like best about the product?
A document-oriented data architecture is used by the adaptable and scalable MongoDB database, which enables dynamic schemas and simple changes to document structure. Comprising grouping, filtering, and converting data is made possible by its strong query language and indexing features. Because MongoDB uses sharding—a horizontal scalability technique that divides data across numerous servers—it is exceptionally well-suited for managing large-scale data and high-throughput applications. Data redundancy and failover are ensured by its built-in replication and high availability features, which also minimize downtime and guarantee data integrity. All things considered, MongoDB is a useful option for contemporary, data-intensive applications.
What do you dislike about the product?
When compared to traditional databases, its implementation can be less resource-efficient and straightforward, which makes it challenging to manage scenarios needing complicated transactional consistency across several documents. Furthermore, inconsistent data in sharded clusters might result in performance bottlenecks and unequal data distribution. Because of MongoDB's flexible design, inconsistent data structures may result, which could affect the quality of the data and complicate application and query logic. For applications demanding higher consistency assurances, MongoDB's default setup for Write Concerns and Read Concerns may not be ideal. Careful customization is therefore necessary. To overcome these obstacles and capitalize on MongoDB's advantages while minimizing its drawbacks, meticulous preparation and knowledge are needed.
What problems is the product solving and how is that benefiting you?
To create data-intensive applications, like IoT storage solutions and social media analytics systems. Because of its document-oriented data format, changing data requirements may be accommodated without requiring significant schema migrations, allowing for agile development and iteration. Due to its scalability, MongoDB can easily expand without compromising speed, making it an ideal solution for managing large datasets and high-throughput applications. Consulting businesses may create complex analytics and reporting solutions by utilizing its advanced querying and indexing capabilities to pull important insights from a variety of datasets. These functionalities are essential for creating data visualization apps, business intelligence tools, and custom reporting dashboards that are suited to the individual requirements of clients.
My experience with MongoDB
What do you like best about the product?
I have been using MongoDB for the past 3 months and I have noticed a few points that I would like to highlight. MongoDB provides great flexibility, object-oriented models, and design. Its scalability is also impressive. I have successfully integrated it with Textastic, and it is working perfectly. Its very easy to use and provides good customer support as well.
What do you dislike about the product?
There are a few points, which can be improved like lack of transaction support, memory usage and learning curve
What problems is the product solving and how is that benefiting you?
It's solving my problems in several aspects, such as flexible schema and scalability with high performance. MongoDB is a highly document-oriented model, which allows me to represent complex data effectively.
Free for development, scalable, and user-friendly for connecting with frontend and backend technologies
What is our primary use case?
We store all our data in MongoDB. Our frontend application is .NET, our backend is .NET, and the database is MongoDB.
We have two products running on MongoDB: a financial expense management solution and a sustainability product.
What is most valuable?
It can store data as a flat file, similar to a file system. It's called Atlas GridFS and it works very well.
MongoDB is a very good database. The Community Edition is free, which is cost-effective for development.
The API support is excellent for integration.
What needs improvement?
From an improvement standpoint, MongoDB can improve security.
There are some challenges from a security point of view. Since the file can be easily accessed, there should be more security features. The data should be encrypted in some form to prevent unauthorized access.
For how long have I used the solution?
We've been using MongoDB for three to four years.
What do I think about the stability of the solution?
I would rate the stability a nine out of ten.
We haven't seen high volumes of data yet. Our solution is for expense management, not a full ERP solution. So far, the system has been stable with the current number of users.
What do I think about the scalability of the solution?
It should be scalable and easily work with other databases like SQL or Oracle. We shouldn't have trouble converting the data.
I would rate the scalability a nine out of ten. Some security features are still under development.
MongoDB isn't for our internal users; it's for our customers. Depending on the organization, it can go up to ten thousand or even a hundred thousand users. We have a lot of customers using our applications built on MongoDB.
We are a young company, only five years old. We recently started this product, but we know that around a hundred people are using it in one of our products for web and mobile.
How are customer service and support?
We have a very strong internal technical team that manages everything. We haven't needed any support from MongoDB because our team is proficient in using it.
Which solution did I use previously and why did I switch?
My team only recommended MongoDB. We haven't worked with other databases for our current projects. I have worked with SQL Server and Oracle in the past as an SAP consultant, but those were for ERP systems, not application development.
How was the initial setup?
MongoDB's setup is very easy. We plan to only use MongoDB for our future database needs.
It works very well with the .NET and Angular platforms due to the flat file support. So, we went with that option.
What was our ROI?
The main benefits include cost savings and speed. The application runs fast, and accessing data is quick.
ROI is very good.
What other advice do I have?
It's very easy to manage for our technical data analysts.
Overall, I would rate the solution a nine out of ten. I recommend using MongoDB because it's free for development, scalable, and user-friendly for connecting with frontend and backend technologies like Angular and .NET.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Microsoft Azure
Great NoSQL DB with few limitations
What do you like best about the product?
MongoDB is great NoSQL document db that offers features horizontal scaling, schema less architecture, good third party support
What do you dislike about the product?
Limited support of ACID transactions and complixity of sharding
What problems is the product solving and how is that benefiting you?
We are using MongoDB to track and report on the employees activity. This involves aggregation queries, geospatial queries and stored scripts to support an APIs for in house web application.
Serves as a general-purpose database and provide IoT integration
What is our primary use case?
We primarily utilize MongoDB Atlas for tasks such as IoT integration. Additionally, it serves as a general-purpose database that aggregates analytics data before transferring it to a data lake. Its versatility allows for various applications, providing flexibility and ensuring the availability of essential data across different systems. While it is used in diverse contexts, many use it for IoT-related initiatives.
How has it helped my organization?
We prefer MongoDB Atlas over SQL because most of the data generated with IoT devices is unstructured. This gives you flexibility; you don't have to define specific schemas all the time, and sometimes, the structure of the object varies.
It improves data management along the same lines. MongoDB Atlas supports structured data with IoT projects.
What is most valuable?
MongoDB Atlas was explicitly designed to support IoT applications. Many databases offer features tailored for IoT use cases.
What needs improvement?
One area for enhancement is containerization. They could explore ways to facilitate deploying MongoDB containers within the platform.
For how long have I used the solution?
I have been using MongoDB Atlas for five years.
What do I think about the stability of the solution?
I rate the solution’s stability a nine out of ten.
What do I think about the scalability of the solution?
Two people use this solution because they work with sensors and other variations of IoT.
I rate the solution’s scalability a nine out of ten.
How are customer service and support?
The tool provides a forum where users can engage with experts. These experts offer assistance tailored to your specific needs, whether you're focused on product-centric queries or diving deep into particular use cases. Ultimately, the support you receive depends on your requirements and the extent of your experience with the platform.
How was the initial setup?
The initial setup of MongoDB Atlas is straightforward. The user-friendly UI guides you through the setup process seamlessly. It would be beneficial if they could maintain this simplicity across different operating systems. Additionally, if they can streamline the process to easily deploy with containers, it would greatly enhance user experience and make life easier.
What's my experience with pricing, setup cost, and licensing?
MongoDB Atlas offers various options based on your needs. It can accommodate both, whether you require the enterprise version with advanced features or prefer to start with an open trial version.
What other advice do I have?
Security is primarily organized around organizational principles, allowing you to customize and adjust each tool according to your specific security policies. I recommend the product. Every product serves a purpose as long as it addresses the right problem. MongoDB Atlas has proven particularly effective for applications such as analytics and IoT, making it a recommended choice for those use cases.
Overall, I rate the solution a nine out of ten.
