MongoDB Reviews

I use MongoDB in our company since our overall data is stored on it. My company uses the tool as a back-end database.

The most valuable features of the solution are that it appeases our company's needs and is quick.

The dashboard is an area of concern in the solution where improvements are required. The price of the product may be a concern for the customers who use it, so improvements may be required in the pricing model.

I have been using MongoDB for more than ten years. I use the solution's latest version.

Stability-wise, I rate the solution an eight out of ten.

Scalability-wise, I rate the solution a seven out of ten.

It is always important to ensure that users use the latest version of MongoDB if they want to use the scalability features of the product.

There are more than 1,000 users of the solution.

My company plans to expand the number of users of the product.

MongoDB's technical support team is responsive and helpful.

I rate the technical support an eight out of ten.

Positive

The product's initial setup phase was quite easy, but for some use cases, it was a bit difficult.

The solution is deployed on the private cloud services offered by AWS.

The solution can be deployed in a couple of hours. The product's initial deployment phase can be taken care of in an hour, and if any further deployments are required after that, it takes less than an hour.

Six to seven engineers are required to take care of the deployment and maintenance phases of the solution.

The integration capabilities of MongoDB are fine for the solutions that we use in our company.

The tool's vendor takes care of the product's maintenance.

I rate the overall solution an eight out of ten.

Our company uses the solution for small functions that contribute to some projects. The solution is part of our whole company architecture. Some projects might not touch the solution but the data is always there when needed. 

The reports are useful for controlling the load of our whole architecture. We compare different reports to different levels, applications, and modules of our whole architecture. 

The solution could include more integrations with other platforms. 

One customer is a hospital that uses a specific program with certain authorizations. The solution may not be able to integrate because the authorizations are different. 

I have been using the solution for eight months. 

The solution is stable. 

The solution is scalable. 

We previously used another database but it was not proper for our tasks. The solution provides us with the proper resolution and results. 

The setup is very easy. 

I recommend the solution if you intend to tie it to your business architecture. I rate the solution a six out of ten. 

We are using MongoDB as the database on our private cloud, which is AWS in Frankfurt. We monitor different banks adopting cloud in our infrastructure with confirmation and approval by the local regulator.

It's mostly all related to our digital part of the bank. We are using MongoDB for the process of onboarding new products. When we are actually calculating proposals for mortgages or complex financial products, we must consider that calculation across many sources. Some are internal. Some are external. We are using MongoDB to support the calculation, or proposal calculation, on our web digital processes.

It has given us a chance to explain to people that once the bank made the decision to migrate some processes, applications, and data into the cloud, it was a benefit. It's not only about the change of process and application components. It's also about changing the data ownership and data operation. It went hand to hand, actually, to start training them that there is something beyond Oracle and SQL databases. With Mongo, our team was happy to get a chance to learn something new.

However, once some people learned the solution, we did lose them to someone else. It shows how popular it is not only in our organization but in other places as well. 

We are actually taking MongoDB as serious database tech. It has visible benefits, actually, in terms of price of ownership if you compare it to, for example, Oracle. When we have some processes which really don't need Oracle, we use MongoDB as the first option to see if it wouldn't be cheaper to leverage.

Oracle is stronger in some specific features. For example, the remote cluster when you need to synchronize the enormous amount of data between two data centers and so on. It's that Oracle RDC and Oracle GoldenGate which are actually about the data replication which can be supported by the nature of the database scheme.

We are actually validating each process and also new processes in what we call the operational tier, and if you are having the business-critical processes which need business-critical operative data, we actually prefer Oracle over MongoDB.

MongoDB is the second option for non-critical processes at the moment. We do not yet trust it with critical items.

We'd like information about client onboarding experience and success stories. It would help to have something to show to internal stakeholders. We need some use cases from the outside to begin to open discussions on how we can use this tech in more ways in the future. 

It started during the HR transformation. I would say we started using it four years ago.

For the scenarios we have chosen, it's ranked as stable. We also made what we call disaster recovery scenarios to be able to replicate MongoDB content after failures. So far, it's been very good. It's fast.

We can scale. It went hand in hand with our AWS journey and the cloud infrastructure. I remember one scenario which involved a quite popular product in the Czech Republic. It was for savings accounts. We were actually able to predict the number of interactions being required during the phase of the product opening. We prepared the infrastructure from MongoDB and after that period of time, it was shrunken back to the original size. It scaled up and down exactly as we needed it to.

We have seven internal people including analysts and data engineers working on the solution. They are creating tables and preparing the data loads.

We use it quite a bit now. We take it as the second option for initial test requirements in regards to the data infrastructure. The Oracle Database is not the first choice anymore, except for the Tier 1 pieces of processes.

I am not involved in the troubleshooting. I don't directly deal with technical support.

We also use Oracle. Previously, a long time ago, I also used Teradata.

In Asian companies, Oracle is very expensive to use and adopt.

We started using Mongo as it was stable and easy to adopt.

The first time we deployed the solution was actually a limited implementation to support the proof of concept. When we had some objectives when it came to validating how fast we were able to prepare Mongo at AWS, it was quite simple. 

The second part was actually to handle the initial training of people for operation and administration. Now we actually have some results which prove that the MongoDB way is a positive way and this is what we ended up using for other scenarios.

I would say that if you would were looking for 100% of the data in the cloud, MongoDB would currently be at 50%.

The initial proof of concept was scheduled for three months.

We did the cloud adoption in-house. We did have help with a few complex elements. It was supervised and everything was finished by the internal code team to improve their skills and learn what was needed to have BAU, business as usual.

The ROI is fair. I'd rate it 2.5 out of five in terms of getting a return on investment. It's something, on our side, that we still have to fully adopt, however. 

I was trying to compare pricing in terms of how much it would cost to do a TCO. We are counting TCO five years ahead - the total sum of money. It was 2.5 times cheaper than Oracle. I would say it's stable and the pricing is reasonable.

This is the first time we've adopted the cloud and therefore it's hard to truly gauge how much it will be a year out. It could change. It's difficult to accurately predict.

We faced some extra costs for what we call the L2 and L3 additional support.

We are customers and end-users.

We are likely on the latest version right now. 

You can adopt this tech very easily on your private cloud. AWS is actually broadly supporting and it's not only us but also a lot of other industries. MongoDB is not unknown. There are a lot of people that have experience with it, however, it's very important if you have a company that is evaluating something, to have the ability to execute. 

If you have some local vendors, if you have international vendors, if you have some integrators that are able to use it and to help you use it, MongoDB is a good choice.

I'd rate the solution five out of ten.

I use MongoDB whenever I want to use non-relational data. I use the solution to make a non-relational database or objected data for my personal project related to social media. MongoDB stores the JSON data, and it's easy for me to understand because I'm a JavaScript Developer.

MongoDB should improve its data loading part. If I update data with MongoDB via the browser, the loading takes a lot of time when I want to use the updated data. The loading is further slowed down if my internet is slow. We use MongoDB Compass to avoid these types of issues.

I have been using MongoDB for four years.

MongoDB is a stable solution, and I haven’t seen any bugs in it.

I always connect the solution using the same method. I recently tried to connect to MongoDB, but I couldn't do so. I contacted the technical support team, and they told us that our server is an Asian server. They told us the issue would be fixed automatically in two or three hours. I waited for the server to be fixed and then resumed work. I did not directly contact the support team. I asked another developer facing the same problem to contact the support team.

The initial setup of the solution is easy for me, but it's not easy for any beginner to learn MongoDB. MongoDB gives us the connection string that I connect to the node to ensure the connection is done. MongoDB sometimes gives us an IP problem if their IP and my IP are not the same. MongoDB uses a private IP, but I can use a global IPL.

Sometimes, beginners can't understand why the database is not working despite them connecting MongoDB the way I showed them. Sometimes, my junior developer comes to me and asks why the database is not working. By default, MongoDB sets a strict IP address. Then, I edit the solution's private IP and change it to our global IP. Using a MongoDB connection string is a bit hard for a beginner, but it gets easier as they practice it two or three times.

MongoDB is a non-relational database that is deployed on the AWS and Azure cloud. I recommend PostgreSQL or MySQL to users who do not want to store data in JSON format. I also recommend MongoDB to users who want to build a project that stores JSON-type data in the database. MongoDB makes it easy for me to read the data from a JSON perspective and fetch the data from the database.

Connecting to MongoDB will be easy if you learn the queries and how they connect or manipulate data. For the first time, you have to learn the solution's queries and data flow to use it. The learning process for MongoDB is easy because it has easy-to-understand documentation. Any beginner can read the documentation and try to use the solution.

Overall, I rate the solution a nine out of ten.

I use MongoDB mainly on the back end. We use it in my company for the database, and I also use it on my side projects.

MongoDB is a NoSQL tool that gives us much freedom to manipulate how the data works.

MongoDB should support TypeScript.

I have been using MongoDB for about two years.

I haven't had any issues with the solution's stability. However, our company faced an issue where the tool was down for two hours.

I rate the solution’s stability an eight out of ten.

MongoDB is a very scalable solution. About 10,000 users are using the solution in our organization.

I would recommend the solution to other users because it's scalable and easy to learn. The solution's documentation can be rigid and hard to understand initially. Users should use an ORM or ODM. They should use Prisma or Mongoose as the starting point for using MongoDB. MongoDB is easier to manipulate. The easier the onboarding, the harder the maintenance.

Overall, I rate the solution an eight 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. 

Our company uses the solution to manage a large sum of data. It is clustered rather than tabular so we can use the solution for large data. 

We currently have four users. 

The solution is able to handle large data. 

The solution does not hold data in tabular format like SQL does but rather clusters data so that it can link on a large scale. 

The solution can be a bit tough to set up if you don't have knowledge about how the database works. 

I have been using the solution for three months. 

The solution is pretty stable with no issues. 

Based on our experience so far, scalability is rated a nine out of ten. 

I have not needed technical support. 

The setup is pretty easy if you have some idea of how it works. It can feel a bit tough if you don't have knowledge about the database. 

We implemented the solution in-house. Everything is in the cloud and deployment takes even less time than MySQL. The solution does not require a lot of maintenance. 

The solution is open source so is free. 

It is important to learn how the database works, how to configure data, and how to transfer data. Once you know these basic things, you are good to go. 

I rate the solution a nine out of ten. 

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.