MongoDB Reviews

We use MongoDB in different products. The first is a Business Process Management System (BPMS) that we have developed for ourselves. MongoDB stores all of the data for business flow management.

The second product is in the capital market. We have implemented it to use all of the stock-related data.

We have also developed an online shipping product, using MongoDB for storing product features.

The most valuable feature is that you can store unstructured data, which is helpful when you don't know what the best structure should be and you cannot use a relational database because of that. For example, in our online shopping product, different products have different features and there is no structure for all of the data.

The usability is good.

Compared to a relational database, the performance is good.

The performance can be improved. While it is good compared to relational-type databases, it could still be improved.

Stability-wise, there is some room for improvement.

I have been working with MongoDB for between four and five years.

If you take care of the application and check everything then it will be stable. However, if you do not maintain it properly and do not have support then stability will be a problem.

We have not tried to scale our implementation of MongoDB.

We do not have direct support for this product. Instead, we have used the community-based resources that are available on the internet. For example, we have searched for questions and taken advice from the community in order to resolve our problems.

We may have used InfluxDB for some reason but I don't recall any of the details.

The initial setup is simple and not a problem to complete. I don't recall the exact length of time that it took to deploy, but I think that it was completed within one or two days.

We deployed MongoDB ourselves.

We have two administrators who maintain and work with it on a daily basis.

We use the open-source version, which is available to use free of charge.

My advice for anybody who is considering MongoDB is that when we want to have flexibility in storing our data, I recommend using it. We can store anything, in any format, in any size, and accessing the data is the same speed. In the case where you have structured data or it is in a unique format, this is not the product that you use.

In summary, this is a good product and it has been very useful for our purpose.

I would rate this solution a seven 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.

I have used the product to store and manage data operations.

MongoDB is simpler to learn and implement than traditional SQL solutions like MySQL.

The product's data consistency could be more efficient than traditional SQLs.

I have used MongoDB for a year while working on a project. I was using the latest version.

MongoDB was stable and much faster than traditional SQL.

There were five MongoDB users in our organization working in different teams.

I was working with MySQL before. I decided to use MongoDB rather than other products to learn something new. It is easier to learn and implement than other databases.

The learning process for initial setup is easier compared to traditional SQL. Someone without prior experience working with it can learn the process quickly.

MongoDB is an open-source product. We don't have to pay for the licenses.

I advise others to evaluate a lot of other databases. MongoDB worked fine for my project. However, I would have selected a product besides MongoDB to improve my skills and learn something new.

I rate it a six 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.

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 use it for searching. For example, we use some files and documents that are stored in MongoDB, and we use it sometimes to search for certain key words. We also use it to search within the documents that are stored in MongoDB.

MongoDB is scalable and stable. The initial setup is very easy, and deployment and maintenance can be done by one person.

I think it would be good to have more search options such as an index resource. This will provide more options and resources to do advance searches.

Criteria and filters would be good too as they will help us find what we are looking for. Filters will be useful if you want to filter something to a dashboard according to certain criteria.

I have experience with MongoDB for about six months.

MongoDB is stable. We have had no technical issues with it.

It is a scalable solution.

Technical support has been good.

Installation is very simple. It can be done in a few hours. We needed only one person for deployment and maintenance.

Our customers pay for yearly licenses for MongoDB.

It's a very good product, and I would rate it at nine on a scale from one to ten.

When the company started, MongoDB was our primary database.

It offers great flexibility where developers can define any key and assign a value to it. This means that there is very little that one has to plan in terms of designing the schema upfront, so developers enjoy a lot of flexibility. Now that we have more use cases for which NoSQL is not suitable, we are trying to move those workloads out of MongoDB.

MongoDB is extremely developer-friendly because when you are starting, there is very little time needed upfront in terms of planning. Whenever a developer wants to build a certain feature, they simply define a key and a value and that's it.

It is very easy to create an index on a field that you want to have searchable.

All of the documents are stored in JSON format, which gives developers a lot of flexibility.

MongoDB should not be used for reporting, analytics, or number-crunching tasks.

The pricing should be improved because the whole design is around replication of data, so in terms of storage costs, in the long run, it will be expensive. The amount of storage grows very quickly when compared to other databases that store data in normalized form. If there were a way that some data could be partitioned or moved into cold storage then it would be very good.

We have been using MongoDB for about four and a half years.

There are bugs in the system but they are not very significant. We have found a workaround for each of those bugs and we have been running the full-scale production cluster for more than four and a half years. As we haven't had any issues, I would say that it is pretty stable.

This solution is used constantly by both us and our customers, every second of every day.

We are not looking at increasing our usage. Rather, we will be moving some of our workloads off of MongoDB. Ultimately, usage will be at a standstill or perhaps even reduced.

This is a scalable solution. We have close to 100 developers who use it. In addition, our entire business makes use of MongoDB. Everything the customer does makes use of this solution, so I would say that we have at least 100,000 users.

Because we are using the Community Edition, we don't have any support whatsoever.

We did interact with them for MongoDB Atlas, and we are still in contact with them to see if we can take something into production a couple of quarters from now.

We did not use another NoSQL database solution prior to MongoDB.

When we installed MongoDB the initial setup was complex. However, now with Atlas, it is very easy. It took us less than a week to deploy and now, with Atlas, there are a lot of things that you don't need to know that was required four years ago.

I did the original cluster deployment on my own.

We are using the Community Edition of MongoDB. However, we would be happy if the pricing for the full version were more competitive.

We use a lot of different database products and the choice depends on the use case.

With respect to NoSQL, we did not evaluate other vendors because when we implemented this solution four and a half years ago, it was the only scalable NoSQL database. This made it a rather obvious choice for us at the time.

The features that I have looked for are in this solution and we are using an older version. The current cloud-offering, MongoDB Atlas, has even more features. It would be a natural fit for us, but it will not be easy to move because we have a lot of dependencies. We have to update drivers, isolate collections, and take care of other issues before we can switch.

My advice for anybody who is implementing this solution, or any other database, is to take care to plan your indexes because it is extremely important. Spending some time designing the document structure in the initial phase will certainly help you in the long run.

I would also suggest that in terms of sharding, try to think about it as early as possible so that when you are ready to scale, it will certainly help to reduce the workload.

Do not rely on MongoDB for any of the analytics use cases. Aggregation works well but do not use it for your reporting or analytics or number crunching-related tasks.

I would rate this solution a nine out of ten.

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.