MongoDB Enterprise Advanced Reviews

I use MongoDB whenever I want to use non-relational data. I use the solution to make a non-relational database or objected data for my personal project related to social media. MongoDB stores the JSON data, and it's easy for me to understand because I'm a JavaScript Developer.

MongoDB should improve its data loading part. If I update data with MongoDB via the browser, the loading takes a lot of time when I want to use the updated data. The loading is further slowed down if my internet is slow. We use MongoDB Compass to avoid these types of issues.

I have been using MongoDB for four years.

MongoDB is a stable solution, and I haven’t seen any bugs in it.

I always connect the solution using the same method. I recently tried to connect to MongoDB, but I couldn't do so. I contacted the technical support team, and they told us that our server is an Asian server. They told us the issue would be fixed automatically in two or three hours. I waited for the server to be fixed and then resumed work. I did not directly contact the support team. I asked another developer facing the same problem to contact the support team.

The initial setup of the solution is easy for me, but it's not easy for any beginner to learn MongoDB. MongoDB gives us the connection string that I connect to the node to ensure the connection is done. MongoDB sometimes gives us an IP problem if their IP and my IP are not the same. MongoDB uses a private IP, but I can use a global IPL.

Sometimes, beginners can't understand why the database is not working despite them connecting MongoDB the way I showed them. Sometimes, my junior developer comes to me and asks why the database is not working. By default, MongoDB sets a strict IP address. Then, I edit the solution's private IP and change it to our global IP. Using a MongoDB connection string is a bit hard for a beginner, but it gets easier as they practice it two or three times.

MongoDB is a non-relational database that is deployed on the AWS and Azure cloud. I recommend PostgreSQL or MySQL to users who do not want to store data in JSON format. I also recommend MongoDB to users who want to build a project that stores JSON-type data in the database. MongoDB makes it easy for me to read the data from a JSON perspective and fetch the data from the database.

Connecting to MongoDB will be easy if you learn the queries and how they connect or manipulate data. For the first time, you have to learn the solution's queries and data flow to use it. The learning process for MongoDB is easy because it has easy-to-understand documentation. Any beginner can read the documentation and try to use the solution.

Overall, I rate the solution a nine out of ten.

The primary use case is data retrieval. It allows for easy retrieval of data as all the required information is stored within the document. This becomes particularly useful as the company scales, preventing queries from becoming sluggish.

Working with it extends beyond database skills. Utilizing additional tools such as ML frameworks (e.g., TensorFlow), languages like Python for data analysis, and platforms like Apache Spark for distributed computing can enhance one's capabilities in extracting meaningful insights from data.

It facilitates the generation of heatmaps for graphical data analysis. This can be valuable for visualizing patterns and trends in data. While other databases like Cassandra may also serve this purpose, MongoDB stands out for its simplicity in handling complex queries and graphical data representation.

It has certain limitations when it comes to handling hierarchical data, enforcing relationships, and performing complex joins, which should be taken into account when designing databases for applications with intricate data requirements.

I have been working with it for a year now.

It is highly stable. I would rate it nine out of ten.

It emerges as a favorable choice for customers seeking efficient data storage and scalability. On a scale of one to ten, I would rate it at eight.

I have been working with both MongoDB and HIVE and the choice between them depends on the specific requirements of the client. While I've been actively engaged with both databases, the preference depends on the nature of the data and whether file storage is required. If data retrieval is the primary focus without the need for file storage, I opt for MongoDB. On the other hand, if the client requires storage for both data and files, HIVE becomes the main choice.

I would rate the initial setup six out of ten.

I only used the open-source version.

Opting for MongoDB could be beneficial, especially for storing large volumes of records, even for transient data. The decision hinges on the nature of the data itself. If there is a significant amount of metadata, it becomes a preferable choice for its scalability and superior query performance. It's important to anticipate future operations; for example, if there's a current load of ten thousand audio and video files, MongoDB can efficiently handle it. Overall, I wold rate it eight out of ten.

Our company uses the solution for small functions that contribute to some projects. The solution is part of our whole company architecture. Some projects might not touch the solution but the data is always there when needed. 

The reports are useful for controlling the load of our whole architecture. We compare different reports to different levels, applications, and modules of our whole architecture. 

The solution could include more integrations with other platforms. 

One customer is a hospital that uses a specific program with certain authorizations. The solution may not be able to integrate because the authorizations are different. 

I have been using the solution for eight months. 

The solution is stable. 

The solution is scalable. 

We previously used another database but it was not proper for our tasks. The solution provides us with the proper resolution and results. 

The setup is very easy. 

I recommend the solution if you intend to tie it to your business architecture. I rate the solution a six out of ten. 

We use MongoDB for handling document-based databases, specifically for sending unemployment forms using Form IO. 

In remote areas where technology is not widely available, the forms can be scanned and uploaded, and they are stored as key-value pairs in the MongoDB NoSQL database.

MongoDB allows us to store unstructured data with flexibility. It has enhanced our ability to file unemployment processes for individuals who cannot access the system to create a claimant ID.

The most valuable features of MongoDB include the flexible schema for storing data, its replication capabilities with high availability through a replica set setup, and horizontal scalability using sharding.

There was a need for integrating relational database capabilities, however, MongoDB has introduced a relational converter that allows conversion between SQL and NoSQL.

We migrated to MongoDB back in 2019 during the COVID period.

MongoDB scales horizontally using sharding, which is efficient and enhances performance by reducing load and increasing speed.

We used a traditional SQL database before moving to MongoDB. My exposure to MongoDB's ability to handle unstructured data was compelling.

The initial setup was easy, largely due to my preparation for certification and the support from site reliability engineers and architects.

The implementation was assisted by a site reliability engineer, and I prepared a playbook for guidance.

I am not entirely aware of the exact pricing details, however, MongoDB is a fairly valued product.

MongoDB is an excellent choice for those seeking flexibility in storing unstructured data. Its replication, high availability, and horizontal scaling through sharding make it very valuable. Understanding JSON and gaining certification can greatly aid in leveraging MongoDB effectively.

I'd rate the solution ten out of ten.

Our primary use case is mainly for web applications.

The document-based style is valuable as it allows for easy addition of sub-documents, unlike a relational database. It adds flexibility and facilitates data management. The geospatial index feature is also useful for dealing with latitude and longitude data.

The free tools, like MongoDB Compass, could be enhanced. This is especially relevant for the IDEs or similar tools.

I have been using MongoDB for about ten years or so. I am not certain of the exact years, however, it has been since almost version three.

MongoDB is quite stable. I haven't encountered any application-breaking problems with it. It handles backups well and doesn't have significant disadvantages.

I rate the scalability of MongoDB as eight out of ten. It is used for very large databases and is very useful, although we don't use it much.

MongoDB has tech support and customer support, however, I have not personally contacted them.

Positive

I have evaluated RDBMS, MySQL, and Azure SQL previously. MongoDB's advantage is its flexibility as a document database, though it doesn't mean it's better than other databases. It depends on the implementation.

The initial setup is relatively easy, similar to setting up MySQL or other databases.

I am not sure about the return on investment as I don't have knowledge regarding the purchase and related aspects.

MongoDB is free of charge. that said, there is also a paid version. We use both free and paid versions.

I evaluated RDBMS, MySQL, and Azure SQL.

To start with MongoDB, I recommend reading their documentation, as it is quite sufficient.

I'd rate the solution nine out of ten.

I am basically a developer and also a freelancer. I take up a lot of freelance projects for which I use MongoDB. I use it for the database system on my website.

The tool provides some free packages for freshers, which is very good because a lot of beginners or students don't want to spend too much money on it. The tool is also user-friendly. I don't make any connections a lot of the time if I use MongoDB in my project.

I previously encountered some issues with the tool, which included downtime issues. Sometimes, the tool goes down temporarily. There are some stability issues in the product.

There are some problems with the tool's website, and it can get laggy, but otherwise, it is pretty good.

I have been using MongoDB for more than a year. I am just a user of the tool.

The tool works most of the time, but it may go down at times. Stability-wise, I rate the solution a seven out of ten.

The tool's scalability is pretty good. Scalability-wise, I rate the solution an eight out of ten.

MongoDB is pretty popular, and we have a lot of documents and support available for it. The community is pretty big for it. I never faced any problems.

I have a little experience with SQL, but. I have major experience with MongoDB because it is well compared to other tools.

The product's initial setup phase is easy.

The product's deployment phase can be done quickly. In a few minutes, we can create a database, get the APIs, and use it without any issues.

The pricing is normal. Price-wise, the product is not too much expensive.

Though the replication features in the product are pretty good, I don't use them a lot.

I definitely recommend the tool to other people. A lot of startups can use it, and some people can already use it. If some students want to do some project, they can use the tool as its pricing is reasonable. The support and stability of the tool are also okay.

I rate the tool an eight out of ten.

I work with multiple personal applications, and for that, I use MongoDB and SQL Servers. Depending on the use cases, I choose MongoDB, as it is not a heavy application. Usually, I use MongoDB for attachment sections because RDBMS is heavy for attachment software. I also use it for assessments. Sometimes, I store data for a time-series database, such as stock market data, which I analyze using MongoDB.

Feature-wise, I like how MongoDB stores attachments because it allows me to store the results of the attachment and pull them up whenever needed instead of having to generate them every time. I can save those results as PDFs and other formats rather than just saving the data and then having to regenerate it. This approach enables me to analyze the attachments and research existing data, making it easier to retrieve information when needed. Overall, MongoDB has helped manage and analyze attachment data.

I cannot comment on how to improve the database since I am not an expert in that field. It is important to note that MongoDB has limitations since it can only be used for specific use cases. For example, for master data, I would want to pick keys using an RDBMS, but for attachments, I would choose MongoDB. Other than that, I am more familiar with RDBMS databases.

I have experience with MongoDB for three to four years and am an end-user of the solution.

It is a stable solution. Stability-wise, I rate the solution a nine out of ten.

It is a highly scalable solution. In fact, a friend of mine who works as a stock market analyst and operates using one of the popular websites in India also uses MongoDB for his work and finds it very efficient. Scalability-wise, I would rate the solution a nine out of ten. From my end, only four to five people use the solution, but from my organization's perspective, around 500 users are utilizing it.

We used to handle technical support ourselves, as the tool was easy to handle, and we didn't need any special assistance. Although we never had to interact with technical support, I would rate it a nine out of ten.

Positive

Previously, I used RDBMS but found it a bit slower. That's why I switched to MongoDB for analytics purposes. I had also tried using MySQL long back before using ClickHouse, but after that, I didn't use MySQL again. While using MySQL earlier, I faced some performance issues while writing a lot of entries. So I shifted to MongoDB, which has been working well for me. Although MySQL is an open-source solution, its performance was lagging. I also tried using Oracle, but it was a costlier option.

The initial setup of MongoDB was easy for me, and I found the community support to be very helpful. I rate the initial setup process a nine out of ten. The deployment process was also quick and only took a day or less. All that was required was to install the solution, which didn't take much time. I deployed the solution on my own, and it doesn't require any maintenance. As a friend and I only use it, it is for personal use only.

I chose MongoDB because it is cost-effective compared to Oracle, which can be expensive. In addition, MongoDB has good performance and has not caused any issues while working with it. It has been a good choice for me.

I recommend MongoDB because I haven't experienced any issues with it so far. Therefore, I would definitely recommend it to others. I wouldn't give the tool a ten out of ten since there is always room for improvement. I rate the overall solution a nine out of ten.

We use MongoDB to build online applications.

The most valuable feature is the speed of MongoDB.

The scalability of the solution has room for improvement.

I have been using the solution for two months.

The solution is stable.

The solution is not really scalable. I give the scalability a six out of ten.

We have ten people using the solution and we plan on increasing the number of users.

The initial setup is straightforward. The deployment time was within one week.

The implementation was completed in-house.

I give the solution a seven out of ten.

Three people are required for solution maintenance.

We chose MongoDB because of the speed.

MongoDB is a good solution and I recommend it to others.

Our company uses the solution to manage a large sum of data. It is clustered rather than tabular so we can use the solution for large data. 

We currently have four users. 

The solution is able to handle large data. 

The solution does not hold data in tabular format like SQL does but rather clusters data so that it can link on a large scale. 

The solution can be a bit tough to set up if you don't have knowledge about how the database works. 

I have been using the solution for three months. 

The solution is pretty stable with no issues. 

Based on our experience so far, scalability is rated a nine out of ten. 

I have not needed technical support. 

The setup is pretty easy if you have some idea of how it works. It can feel a bit tough if you don't have knowledge about the database. 

We implemented the solution in-house. Everything is in the cloud and deployment takes even less time than MySQL. The solution does not require a lot of maintenance. 

The solution is open source so is free. 

It is important to learn how the database works, how to configure data, and how to transfer data. Once you know these basic things, you are good to go. 

I rate the solution a nine out of ten. 

We installed MongoDB on an EC2 instance and used it. 

Use used MongoDB for a NoSQL use case.

The most valuable feature of MongoDB is the ease of connections, aggregation, and queries. Additionally, there is plenty of documentation available for assistance if you require it.

MongoDB should incorporate more features, particularly search functionality, and real-time communication capabilities, to improve the database and provide data listening services. Currently, we rely on the Atlas offering, but it would be fantastic if MongoDB could develop a new solution or updated version that includes these features within its internal database and driver. However, I am uncertain if this would be a viable or profitable move for them, and I am speaking from a mobile-centric viewpoint.

I have been using MongoDB for approximately six months.

The solution is stable. However, I recall instances when the database crashed due to high-volume querying, but this can occur with any database if the queries being run are not optimized for the particular instance.

I rate the stability of MongoDB an eight out of ten.

I rate the scalability of MongoDB a seven out of ten.

We were using PostgreSQL for everything, but it is not the best fit for our needs due to the diverse nature of our data. We switched to MongoDB, as NoSQL is better suited for this scenario.

I have received a return on investment using MongoDB.

The pricing is favorable if you opt to install MongoDB on an Amazon EC2 instance as you won't have to pay for the extra Atlas services and can instead manage the scaling yourself. This allows for a cost-effective solution and using MongoDB on a small scale, I have been able to utilize it for free.

I rate the price of MongoDB an eight out of ten.

I rate MongoDB an eight out of ten.