MongoDB Reviews

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.

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.

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.

Our primary use case has been for maintaining video content and varying it. We are an enterprise-level organization with around 500,000 employees internationally. The company has over 10,000 users of this solution. I'm an integration solution architect. 

The solution is user-friendly with a good object retrieval feature. There are no joins, queries are fast and the product provides helpful drivers. I like the abstraction layers. 

I'd like to see improved scalability and elasticity. Also, the software should have certified container images so it can readily be used in production.

I've been using this solution for two years. 

The solution is stable. 

More could be done to improve the scalability.

Customer support is at a reasonable level. 

The initial setup was pretty simple. It's a good product for academics since it's an open-source solution so it's readily accessible with fast onboarding. Deployment was carried out in-house. There is no maintenance required.

I rate this solution seven out of 10. 

We use MongoDB mainly for data visualization and filtering purposes.

MongoDB's most valuable feature is data visualization.

They could provide more documentation and examples for adding pipeline stages. There could be a feature where commands made in MongoDB could be easily copied and shared in their original format. This functionality would enable seamless transition and compatibility between platforms like Linux and mobile devices, reducing the need for complex filters or Citrix-based solutions.

We have been using MongoDB for five months.

I rate the platform's stability a nine out of ten.

My department has around 50 MongoDB users.

It is a cloud-based version and is simple to deploy.

We evaluated OracleDB and MongoDB. We decided to work with MongoDB as its interface is easier to understand and more universal. It offers ease of integration and simpler configurations compared to OracleDB. It also provides all the essential functionality.

I rate MongoDB a nine out of ten.

My use case for MongoDB is storing logs. Last semester, I worked on a malware and antivirus project, used the deep learning model based on the logs and data from the IDF and FreeRTOS, and stored the logs in MongoDB in a different file.

I store logs in MongoDB for later use, and then I can retrieve the logs and create a model accordingly.

I found that MongoDB is most valuable for storing school-related queries. It's also user-friendly, and I found no difficulty accessing it. Setting it up is easy too.

MongoDB could be more secure.

I've been using MongoDB for one year, but I'm not into creating a full-stack application in MongoDB.

MongoDB is a scalable solution. However, if it's loaded with queries, I can use Docker.

I've never contacted the MongoDB technical support team.

I have experience with MySQL and PostgreSQL, but I'm entirely focused on deep learning, so my team only uses MongoDB and Databricks. I'm not into complicated products, and I know what I can do with MongoDB and how to do it.

The initial setup for MongoDB is basic. It's not complex, but I didn't deploy MongoDB directly into AWS. I used AWS to access the database.

I'm using the free version of MongoDB.

I'm using the database MongoDB.

I'm probably using the latest version of MongoDB because I'm using the latest version of Docker.

I have a team of three working on a project that uses MongoDB.

I recommend MongoDB to others. In my college, almost everyone uses it.

My rating for MongoDB is nine out of ten.

 MongoDB has been installed in our active presentation in Google.

The most valuable features of MongoDB are the variety of translations available and the ability to deploy it on the cloud is useful. The cloud users can access the data, work on the data, and if they want to import or manipulate some data they can.

MongoDB can improve large-size video or media frame operations. There are a lot of customers who want to upload media frames and video games but there is some difficulty. In MongoDB, we are looking out for solutions that are for large-size media files that can be saved and navigated efficiently.

I have been using MongoDB for approximately one year.

MongoDB is stable. It has been more stable in the cloud than what we experienced when we used it on-premise.

We are using MongoDB in the cloud and it is scalable.

We have approximately two clients using this solution.

The support from MongoDB has been great. We had to work with them during the data validation and support was helpful. There were a lot of people giving revisions during the migration and they were working for every dollar paid. We had a good experience with their technical support team.

The initial setup of MongoDB is a little complex. The setup was not complex but migrating the data from the existing resources to MongoDB was tough because we had to do some migration. If there was a better migration tool it would help.

I would recommend this solution to others. Having the solution in the cloud was a very clean process.

I rate MongoDB a nine out of ten.

MongoDB is easy to use. 

It isn't easy to recognize entities with MongoDB. 

The tool's installation is easy for anyone with experience in databases. 

MongoDB's pricing is reasonable. 

I rate the solution a six out of ten.