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. 

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 are using this solution for storage and mapping. We have developed an application for mapping. We source the GeoJSON position for approximately eleven million points.

Our application is made for desktops, and we started using MongoDB for that application.

We have four teams in our laboratory and the other teams are developing their applications to be used with MongoDB.

The primary use of MongoDB is for mapping the application.

The most valuable feature is the geometric information done with GeoJSON. We search the points, and we can perform searches for the data using the RPA for MongoDB. We can ask for points in the geometric shapes or points near other points.

Simplifying the aggregation framework would be an improvement.

Also, the replica system could be improved.

I have been using MongoDB for approximately four years.

We have anywhere from 15 to 20 people using this solution on a daily basis.

This is a stable solution and we are happy with it.

It is possible to scale this solution but it has a problem with the replication.

I have not contacted technical support. We have been able to resolve any issues we have had on our own.

Previously we used MariaDB and we continue to use MariaDB for other purposes. We started using MongoDB to manage non-relational data.

The initial setup was simple and straightforward.

It took a couple of hours.

I am the only one maintaining this solution.

I completed the initial setup and implementation.

I did not use the help of a vendor or integration. I did it on my own.

MongoDB is an open-source solution.

We are a small laboratory and always look for open source solutions or solutions where the licensing is every year. We are prepared to do the troubleshooting ourselves.

The most important part is to evaluate the rest of the ecosystem integrations. When we started, the driver that we used to develop the application was in C++ wasn't relevant. At the start of the project, we had some difficulties because there was no documentation available. There were no examples and no support from the community. 

You have to take into account the languages that you are using. If you are going to develop in the main languages of the solution such as Python, or JavaScript, then you won't have to worry.

I would rate this solution a nine out of ten.

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. 

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.

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.

Sharding is an excellent feature of MongoDB. Atlas is an awesome feature of MongoDB that makes life easy.

People coming from RDBMS should have the flexibility to write queries in SQL that can be converted into JSON queries. This feature is working, but we can still achieve some integration and make it more flexible. It is not as easy as writing direct queries on Atlas. This feature will definitely increase a lot of users. RDBMS users think this is a different query language, MQL, which is uncomfortable for them.

I have been using MongoDB version 6.0 for more than 12 years as a customer.

MongoDB is a very stable solution. The solution is a leader, according to the Gartner report.

In our company, around 2000 to 3000 people are using the solution.

MongoDB’s technical support is awesome.

Positive

We previously used the RDBMS solution, MySQL.

MongoDB has five to ten times better performance than MySQL. MongoDB has a lot of advantages. With MongoDB, you can store any kind of data, including structured, unstructured, and semi-structured data. MongoDB has a lot of benefits over RDBMS.

It is very easy to deploy MongoDB. If it is deployed on-premises, it takes an hour. It does not need any additional prerequisites or configuration details.

We have seen a lot of ROI with MongoDB because it gives five to ten times better performance.

MongoDB's pricing is not reasonable, but it is not as expensive as the others.

The solution's pricing depends on the deal, which includes how long you will use it and the number of deployments. They do not have a fixed cost. However, the maintenance and support cost is included.

I am satisfied with the product.

Our organization has a DBA team of 50 people. However, the work for the DBAs is minimal because MongoDB intends to have zero DBA. They want to develop a product where the need for DBAs is minimized.

Users should approach MongoDB with an open mind, without thinking that it's a different technology altogether and has a different language. Users don't need to develop the application based on a schema. They can develop the application, and the schema will follow.

Overall, I rate MongoDB an eight out of ten.

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.