MongoDB Reviews

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. 

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.

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 are using MongoDB for storing user information and our customer data. If an application requires to save information, that data is stored in MongoDB.

MongoDB has helped my organization by being able to handle large amounts of data. Nowadays, if users are using our application all the data we store in our database. If you're trying to receive the information from the database, it's important we are able to retrieve the result as quickly as possible.

The most valuable feature of MongoDB is the NoSQL database. In a SQL database, we need to join data together with a unique ID amongst other things, but in MongoDB, it's not required. We can directly receive all the information. The performance is very good. Additionally, they have frequent updates.

I have been using MongoDB for approximately two years.

The stability of MongoDB is good.

MongoDB is scalable.

We have approximately seven backend developers using this solution.

The MongoDB community support is very good. I was facing some problems using some queries, so I posted my issue on that community channel, and within one day, I received a solution. The support was very quick.

I rate the support from MongoDB a four out of five.

I previously used MySQL and PostgreSQL, but I had permission and licensing issues with MySQL. I prefer MongoDB over others.

The initial setup of MongoDB is straightforward. We only had to use a few commands to install it.

There are different licenses available to be purchased, such as individual, premium, or enterprise.

I did evaluate other options before choosing MongoDB.

Only one person is required for the maintenance of the solution.

I recommend MongoDB to others.

I rate MongoDB a nine out of ten.

We use this solution for database verification purposes. Typically, we integrate other analytics tools with the solution, like databases and other tools.

The Dynamic Application is a valuable feature.

The analytics needs improvement.

I have been using MongoDB for a couple of years. 

Hundreds of users use the solution at present. 

The initial setup is straightforward.

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

If we don't have relational data we use MongoDB. It is in JSON format, and we can use JSON. Therefore, without relational data, without type coupling with columns, we can use MongoDB. We use it for queries.

The most important aspect is the clustering part. If you have read/write databases, then MongoDB will be easy to use. You can split those databases. We can save the data into JSON without relational data. 

It is very fast - faster than an SQL or MySQL Server.

Therefore, if you have unstructured data, you should go with MongoDB.

I work with Kafka. Kafka is sending a lot of data - millions of records in seconds. It is not easy to just pass it into the SQL Server. Instead, we are sending those drivers to the MongoDB Server, the MongoDB database. it is very fast

You can manage very fast queries with MongoDB in JSON format. 

The clustering is great. You can have multiple clusters in MongoDB.

It is scalable. Technical support is helpful. 

We'd like to have access to foreign keys.

Sometimes we need to be able to delete unintended data from the end user, and we'd like to have that capability.

The solution is a bit expensive.

There can be stability issues. 

I've been using the solution for three years. 

Sometimes you have multiple requests at the same time and there are thousands of millions of data points. There may be performance issues in that case. Sometimes it is stable and sometimes it is not. 

The solution can handle multiple clusters, so the scaling is fine. Sometimes scaling is not required if you have multiple read databases.

I also use AKS and you can use AKS functionality to scale MongoDB services. 

Technical support is okay.

Neutral

We have it deployed on the cloud with a container. 

It is not a complex setup. It is easy to use. You just compose a file and deploy it from there. 

We have one DevOps team that can handle deployment tasks there are three to five people on it.

We have not witnessed an ROI.

The pricing is okay. It's a bit expensive. I'd rate it eight out of ten in terms of affordability. 

We're using something around version three. 

Overall, I'd rate the solution nine out of ten.