MongoDB Enterprise Advanced Reviews

We use MongoDB to build online applications.

The most valuable feature is the speed of MongoDB.

The scalability of the solution has room for improvement.

I have been using the solution for two months.

The solution is stable.

The solution is not really scalable. I give the scalability a six out of ten.

We have ten people using the solution and we plan on increasing the number of users.

The initial setup is straightforward. The deployment time was within one week.

The implementation was completed in-house.

I give the solution a seven out of ten.

Three people are required for solution maintenance.

We chose MongoDB because of the speed.

MongoDB is a good solution and I recommend it to others.

We installed MongoDB on an EC2 instance and used it. 

Use used MongoDB for a NoSQL use case.

The most valuable feature of MongoDB is the ease of connections, aggregation, and queries. Additionally, there is plenty of documentation available for assistance if you require it.

MongoDB should incorporate more features, particularly search functionality, and real-time communication capabilities, to improve the database and provide data listening services. Currently, we rely on the Atlas offering, but it would be fantastic if MongoDB could develop a new solution or updated version that includes these features within its internal database and driver. However, I am uncertain if this would be a viable or profitable move for them, and I am speaking from a mobile-centric viewpoint.

I have been using MongoDB for approximately six months.

The solution is stable. However, I recall instances when the database crashed due to high-volume querying, but this can occur with any database if the queries being run are not optimized for the particular instance.

I rate the stability of MongoDB an eight out of ten.

I rate the scalability of MongoDB a seven out of ten.

We were using PostgreSQL for everything, but it is not the best fit for our needs due to the diverse nature of our data. We switched to MongoDB, as NoSQL is better suited for this scenario.

I have received a return on investment using MongoDB.

The pricing is favorable if you opt to install MongoDB on an Amazon EC2 instance as you won't have to pay for the extra Atlas services and can instead manage the scaling yourself. This allows for a cost-effective solution and using MongoDB on a small scale, I have been able to utilize it for free.

I rate the price of MongoDB an eight out of ten.

I rate MongoDB an eight 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 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.

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.

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. 

I think that MongoDB's search engine should be improved.

My impression is that this is a stable product.

My impression is that this is a scalable product.

When it comes to technical support, I am the same as our reseller. I use community help and google.

My impression is that the initial setup is straightforward.

MongoDB is a fast and safe solution.

I would rate this solution as a whole a seven, on a scale from one to 10, with one being the worst and 10 being the best.

I primarily use MongoDB for personal projects or minor stuff that I have developed for people who are starting. I'm currently doing testing on MongoDB for new features we're developing at my company.

It's super easy to develop a couple of solutions for clients with MongoDB, like a quick web page with no clear data structure that they need to spin up quickly to validate some sort of MDTP.

The MongoDB documentation can be a little complicated sometimes.

I have used MongoDB for three or four years. 

MongoDB is solidly stable. 

I rate MongoDB nine out of 10 for scalability.

I rate MongoDB support nine out of 10. It's pretty good.

Positive

Setting up MongoDB is super easy.

I rate MongoDB nine out of 10. I recommend reading up on NoSQL in general to learn the best practices.