MongoDB Reviews

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. 

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.

We recently had customers asking about MongoDB, so we have started to deploy new environments for that. We have implemented it may be four times. We are implementing it for our customers in our own infrastructure. We have done on-premises as well as cloud deployments. 

Our database team works on the use cases. I work only on the implementation part. I am responsible for getting the clusters up and running. I'm just managing the server and guaranteeing that the clusters are up and running and backing up. I also handle the monitoring.

It is very easy to create a MongoDB cluster. You can deploy three nodes in one hour.

You can do small configurations to enable routing. It is easy to implement.

It should have GUI for managing clusters. MongoDB needs a more powerful GUI to manage clusters and make switchovers. Currently, there is no good, free tool to check the replication to find out if there is a gap. 

It is very stable.

It is very scalable. You can add nodes every day to the replica.

I have no experience with technical support.

It is easy to implement. One person can manage ten managed MongoDB clusters.

At the moment, all customers are using the community version.

I would highly recommend this solution. I would rate MongoDB a nine out of ten.

We primarily use the solution as a database. It's basically used as a storage engine.

The solution is a very dynamic product. It becomes extremely easy for us to support user requirements and we also make use of the simplicity of a cloud redeployment.

The solution is easy to deploy.

The product can scale quite well.

The cloud version of the solution is very affordable.

The solution's most important aspect is its seamless database.

The solution offers excellent documentation.

The on-premises version of the solution is still pretty expensive, especially compared to the cloud version.

The management on the cloud is pretty good, however, the on-premises deployment model is a bit more difficult in this area.

If they want to make their product a little competitive, they'll have to go to organizations and get a bit more commercial in their approach. They need to think about pricing and licensing for RDBMS players. For them to be competitive in the market, they will have to think of strategies other than what they have currently. Their pricing definitely needs to improve.

We've been working with the solution for four years now. It's actually coming up on five years soon.

We've never faced any issues with stability. It's been very good so far. It doesn't crash or freeze, and it's not buggy by any means.

The solution is extremely scalable When we need to expand it out, we know we can do so easily.

We have about five products that factor into the needs of the BFSI segment in India. These proprietary products developed on five or ten platforms. We don't develop MongoDB, we just use it as a storage platform.

Currently, we also use RDBMS. We use Oracle for some other products. We don't just use MongoDB exclusively.

While Oracle is better for transactional services, MongoDB is extremely good at support services. That's the main difference. I have seen people use MongoDB for transactional as well, however, I have never attempted it, so I can't speak to it's capabilities.

The solution is very easy to deploy. The implementation is not complex at all.

The on-premise implementation takes a bit longer. We're looking at a six month implementation for one of our clients, for example.

We handle the implementation ourselves in-house. We don't need the assistance of a consultant or integrator.

For people who can afford it, there are good subscription offers that are available on the cloud as well as on-premises. On-premises is still a little expensive. However, if a company decides to go to the cloud, it is pretty affordable.

If the company is small, there is a community edition that can be taken advantage of. If a company needs to scale quite a bit, they'll need to move up to the enterprise version.

Due to the fact that we are a BFSI focused product company, we typically recommend that users go for the enterprise-level license.

There is also pricing surrounding support. We're in discussions with MongoDB about that now. I don't know the exact costing just yet, however, I know it isn't free.

We are a customer of MongoDB. We don't embed it in our application, however, we recommend it to our clients who use our product.

We're mostly on the cloud deployment version of the solution However, we do have a banking client who requires an on-premises solution. We work with both and have experience with both.

This solution is perfectly suited for companies of all sizes, from small to large. Small companies can definitely use the community version, however, this product offers an enterprise-level license for much larger organizations as well.

I'd advise new users to be flexible and be able to change their mindset when it comes to MongoDB and what is in the RDBMS. there's a bit to unlearn before you re-learn MongoDB. The solution does have a good survey of languages and it's quite good.

Due to the fact that is scales well, I'd rate it eight out of ten.

We used MongoDB to implement a healthcare application into the Amazon Cloud. We deployed that architecture within the South African public health care sector.

One feature that we found most valuable is that it is completely open source - this was majorly important. Because we worked for a nongovernmental organization we had to work with only open source tools. So that was a big selling point for MongoDB. We also needed a document-based DB to build this FHIR application on top of, MongoDB offers. 

Another major selling point was that they're massively scalable. The fact that unlike relational databases, MongoDB allows a lot more scalability and it was more suited for the type of data that we were storing, which was semi-structured healthcare data. It provided very nicely for the standards that we were working - FHIR - which could be interfaced with JSON and Mongo. It had very good JSON capability and storage. Overall, it was a combination of what we were trying to store and the scalability in terms of being able to store a lot of this information over time.

We were quite happy with the product and the actual use of it. We had no particular problem.

In the future, if they could look into supporting FHIR better. FHIR is a healthcare standard. I don't know what that would mean, but, we had to implement a layer on top of it that implements FHIR. But if MongoDB can look into implementing that would be useful.

The two things that were very important for us were basically performance and compatibility.

I have been using this product for about a year.

It is very stable.

We had issues. It wasn't operationalized yet, but our feeling was that it was easy to set up and easy to operate and very stable. So I would say our compatibility and performance are the two things that came up that I know in the project we had problems with. The rest wasn't at any point an issue.

It's massively scalable. It is very scalable in terms of being able to store a lot of this information over time.

In terms of how many users are using this solution, it was a large database with many objects being pumped into it. But, for our purposes, it was just not necessarily the number of users, but the amount of automation being integrated

It was used by the Provincial department of health, or country. So it was basically the nine provinces in South Africa. And each of them had it. It was all the HIV and TB data for all the departments of health in South Africa. It was big.

I can't recall any issues that our technical team ever had. My feeling was that they were satisfied.

The initial setup was very straightforward. It was a pleasure to work with, for everyone. So setting it up, getting up and running, pumping data into it, and actually looking and querying the data was super simple. We were up and running within an hour. We could literally install and start ingesting information into it from the word go. It was very simple to set up and to have tools to actually query and pump objects into it.

We implemented ourselves.

I would definitely recommend MongoDB. I'm hoping MongoDB will continue to be developed from strength to strength because I think it's an awesome tool. I hope that other products, like DocumentDB, will find a way to work with MongoDB to improve the overall stability of the product. It would be good if other services that host Mongo would become more readily available. It was very useful to actually have a hosted MongoDB set up that is maintained by Mongo Atlas.

I would rate it 9 out of 10 because we had very little issues and it did exactly what we wanted it to do.

MongoDB Atlas was the deployment mechanism we went with and that was hugely helpful for us. MongoDB Atlas is part of the MongoDB suite, I think. It's just a deployment of the Mongo. We also deployed it on Amazon using DocumentDB, but we found that MongoDB Atlas worked better in the end.

We use MongoDB for monthly billing of the mobile software we provide to our client, Talent Post. It includes the services they use on their mobile devices.

One of the biggest benefits is the speed and flexibility of the documents, especially when it comes to modifications. It has definitely helped us to function more efficiently.

The best advantage of MongoDB is the flexibility and scalability of the database.

There is a need for improvement in MongoDB's customer support, better support would be great. 

Another feature that I haven't discovered yet but would be useful is a backup and restore process that can handle large database sizes. Right now, I have over three terabytes of data, including logs, which takes a lot of time for snapshot backups.

I started using MongoDB a couple of months ago.

The overall performance is faster than a relational database like SQL. But, the equation function in MongoDB is not as clever as the stored procedure in SQL. It's more complex to write the functionality like a stored procedure in MongoDB.

I would rate the performance of MongoDB a five out of ten.

I would rate the scalability an eight out of ten. I have around 2500 branches of users that use MongoDB simultaneously. We plan on increasing the usage.

I would rate the initial setup a six, where one is for easy and ten is for complex. It is a little complex. It's more complex when we think about deploying MongoDB with the shopping feature. But setting up MongoDB without consideration of shopping would be easy.

The deployment would take a day, but that includes testing. We didn't use any third parties. We deployed the solution ourselves.

I would rate pricing a seven out of ten. It is a bit costly.

I would definitely recommend using the solution.

Overall, I would give it a seven out of ten. The reason is the flexibility it offers, especially for deploying solutions for mobile services. Additionally, it's still considered a new technology in our country, so it's quite trendy.

Our primary use case of this solution is for schema lists. It's easy to populate the data and to get information for summaries and things like that. The second use case is that there is a mainframe and the upgrades on the mainframe can use your CPU time. As the customer is working on the mixed product, it becomes very costly. Using MongoDB internally allows us to divide as much as we can with it. And there is a service provision that I think is much cheaper than continuing the maintenance of the machine. 

The feature I find most valuable, is that it is easy to use. Even a non-technical person will be able to understand it. I also find the integration with other tools very easy.

The price can always be better. I mean, we are a big corporation so it is quite expensive for us. So perhaps they can improve on the price.

I have been using MongoDB for two years now.

MongoDB is very stable.

The solution can be scaled without any issues.

I have not yet contacted the technical support team of MongoDB, but I have great interactions with the MongoDB side. We have our own technical team in our company that takes care of our issues. 

We have used Snowflake before and I can tell you what the difference is between MongoDB and Snowflake. Snowflake is a totally different type of database. It is basically shot across small units and its solutions are only for the cloud. Your access can be private and it can be fast on the queries. Whereas with MongoDB, it takes much longer than with Snowflake if you want to extract. Snowflake is much faster. It has good analytics capabilities, though.

The initial setup was easy and quite fast. The only problem is the provisioning environment within the cloud. Deploying the MongoDB program doesn't take very long. The whole process of deployment needs only one additional person to do its maintenance and to finalize the deployment faster.  

I will rate this solution a seven out of ten because I like the interface and the integration with other tools. In the next version, perhaps they can modernize the storage options. I think they have a very good reputation, from what I hear from our client comments. The program has speed and it has simplicity. If you want to extract the application, the terms of applicability it is good. And you can use the intelligence within the program. 

One of the key component of our system uses MongoDB as its data store. We use it for storing data sent by devices. It is an IoT platform.

We capture more than 30 million records every week in IoT NS. 

MongoDB has been serving us well so far. It is easier to maintain the data with its document-based storage.

• Its capability to do quick, powerful aggregations has caught my attention. 
• The search queries are pretty fast and mean time to get response is around 50-100/ms. 
• The installation is very stable.

Its indexing capabilities could be further improved. The libraries, e.g., Mongoose could still be improved to handle MongoDB. The improvements could be made to intelligence to detect disk storage and prevent MongoDB from crashing.

No stability issues.

No scalability issues.

The setup is pretty straightforward. Just install, create a user, and start using it. 

I felt it was quicker to use MongoDB compared to MySQL.

We implemented it in-house.

We did compare Cassandra against MongoDB, but we faced a few problems while data was restoring with Cassandra and chose MongoDB to avoid such issues.