MongoDB Enterprise Advanced Reviews

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.

We find the query and speed very valuable.

The performance of the solution could be improved.

We have been using the solution for approximately four years.

The solution is scalable, and we will gradually increase the amount of data stored in the solution.

The initial setup is a little bit complex for cluster deployment. Deployment took a couple of days, including testing.

The licensing for the solution is free.

I rate the solution a seven out of ten.

Migrating to MongoDB upgrades the IT environment and puts users in the NoSQL environment, which is faster.

There are some problems with bugs appearing in sharding when the data is too high. MongoDB also needs to update and be more flexible to match up to more mature products like Oracle or SQL.

I've been using MongoDB for three years.

MongoDB is stable and reliable.

MongoDB is scalable.

MongoDB's technical support is quite good.

Previously, I used AWS DocumentDB and DynamoDB.

The initial setup was straightforward, and deployment took around two hours.

We did the implementation ourselves.

MongoDB is a bit expensive compared to its competitors.

I would advise anyone thinking of implementing MongoDB to test the sharding and duplication concepts in your environment with a huge number of data to see how it will work with multiple scenarios or test cases. I would give MongoDB a rating of ten out of ten.

We are using MongoDB for unstructured databases.

The most valuable features of MongoDB are we have a lot of documentation and SQL-based applications that run on it.

MongoDB could improve by not having so many updates and different versions.

I have been using MongoDB for approximately two years.

MongoDB is stable, but there are always a lot of patches and upgrades every now and then.

MongoDB can scale but you will need to pay for the upgraded solution.

I have not contacted the technical support of MongoDB.

The initial setup of MongoDB is simple and the implementation took approximately one day.

We did the implementation in-house.

MongoDB is a free solution. We wanted to have high availability and the subscription cost was quite expensive because the basic one is free and then when you want to have some other replications or other features you will need to pay money. Overall the solution is expensive.

I would recommend this solution to others.

I rate MongoDB a six 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 for the applications. You can save two or three applications but there's a lot of people using those applications. 

MongoDB is cool. There is a difference between relational databases and newer databases like MongoDB. MongoDB is scalable and fast.

It could be much more flexible like SequoiaDB. I would like to see more flexibility in the next release, especially when working with Microsoft Windows. A lot of people struggle with MongoDB because of their Windows versions. But Linux is faultless and mostly runs nicely.

I have been using MongoDB for about five years.

MongoDB is a stable solution.

MongoDB is a scalable solution.

Customer service depends on your subscription. Suppose it's open-source, then hard luck because you won't get any support. But if you are paying for it, you can get some tech support. However, MongoDB's open-source community is also quite helpful. I'm satisfied with it.

The initial setup is straightforward. 

We implemented this solution by ourselves. One engineer is enough to deploy and maintain this solution.

You only have to pay for the paid version, not the open-source version.

I'll recommend MongoDB to potential users any day.

On a scale from one to ten, I would give MongoDB a nine.

We do payroll for government workers. One service we provide is called e-Payslip. You go into the portal, create an account, and download your payslip for the month. If you have to do something that requires you to submit a payslip, you can go to the portal and get your payslip electronically. 

We also have what we call the ESPV. This allows unit managers to validate workers before they are paid for the month. It's an attempt to remove ghost names from the government payroll, so there's a cycle. At some point, somebody who is actually working must be validated in the system, and then the unit head confirms. This is checked by HR before salaries are paid, so you have to be a validated worker before your salary is paid. 

I think that MongoDB isn't too structured, and that's good for our technical team because they are able to search through the database better than if they are using SQL Server.

I feel that most people don't know a lot about MongoDB, so maybe they could add some more documentation and tutorials. In general, I think they should do more to publicize the solution because when I'm in a meeting and I start talking about migrating to MongoDB, people don't know what I'm talking about.

I've worked with MongoDB for maybe two years. In fact, we recently upgraded and moved everything from SQL Server to Postgres and MongoDB. We went live just about a month ago. This was supposed to be the solution to all our problems, and we are in the process of testing to confirm that we are fine. 

MongoDB is stable. 

We mostly used Microsoft databases in the past. We started with Access and Microsoft SQL Server. I've also used Innovation together with SQL Server.

I'll give MongoDB a 10 out of 10. We are getting positive feedback, so far.

Our primary use case of MongoDB was development. We used it from a developer point of view, writing the platforms and storing some data. It was deployed on the AWS cloud. 

One of the first things I noticed when I had my first experience with MongoDB was how easy it was to use. I was expecting more difficulties or at least some challenges, but it was very, very easy to use. It's great technology, performs well, and is very convenient. 

MongoDB is a very useful and convenient choice, but sometimes for more complex projects, there are certain niche requirements that appear, so using a different tool could be beneficial. It raises the complexity of the architecture, but it could be beneficial to the world, the features, the ease of the features which are being implemented. 

My experience with MongoDB is pretty recent, maybe for three years. 

This solution is stable enough. There isn't much maintenance involved—we're just installing some software and then using it—especially since I'm using it from a development point of view. 

I've heard that MongoDB is pretty scalable, but we never did any big deployment. I've read a lot about how it scales and can handle huge data. 

I have never contacted MongoDB's technical support. 

The installation is quite straightforward. I have it installed on my personal laptop and it's very easy to do. It took just a few minutes. 

There are two or three DevOps guys who are involved with and responsible for all the deployments and setups for the whole project. 

I implemented this solution myself. 

We also considered Cosmos DB. 

I rate MongoDB a nine out of ten. If I put it this way: "Can I trust this technology to perform well in a complex project?," I can certainly trust MongoDB. I have been working with some graph databases as well, and MongoDB was my first touch with noSQL technology. I think I like it even more now, after these experiences I had. 

I use MongoDB from a development point of view. For some projects, we use Docker on local environments. MongoDB actually starts in some Docker microservices where we don't run the whole platform, we're actually running locally or maybe part of the platform. With this container, we don't need to do many things with the image in Docker, we're just developing the platform. And then the deployment and scale are managed by the DevOps guys, who do their magic. We use Azure in some projects, but we mostly use AWS.