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.

We primarily use MongoDB as a database to handle large volumes of data. It's useful when we need to manage millions of records quickly.

The cloud solution offered by MongoDB, known as Atlas, has been invaluable to us. It provides a good, user-friendly interface. The ease of use and scalability make it stand out compared to relational databases.

Improvements could be made in query optimization, particularly when performing lookups or joining tables. Input functions to restrict the amount of data passed in pipelines would be beneficial for this purpose. Additionally, enhancing the documentation to make it more beginner-friendly is crucial. As someone with seven years of experience with MongoDB, I find the ecosystem intuitive, but newcomers often need help with the documentation. 

We have been using MongoDB for seven years now, and we are currently using the latest version.

The platform has good stability.

We contacted the MongoDB team for assistance whenever we encountered issues, particularly when optimizing queries that took too long. They helped us understand the root cause of the problem and provided us with discounts on certain occasions. For instance, when we accidentally used a larger instance, which resulted in higher costs, they understood the situation and offered us a discount to mitigate the expense.

Positive

We chose MongoDB over other solutions because it can handle large volumes of data and is flexible in data manipulation.

The initial setup process is easy.

The product is affordable, but I don't have direct comparisons with other products as I haven't been involved in the billing process.

The NoSQL structure, particularly the document-based data management, has made data management easier for me. MongoDB's approach to handling data in documents rather than traditional tables has been particularly beneficial.

MongoDB's document-oriented model improves development speed by providing each document with its built-in key or ID, similar to a primary key in relational databases. This inherent ID facilitates faster execution of operations, such as searching for specific documents. Additionally, it allows for creating additional indexes, further enhancing performance. The familiarity of JSON-like structure makes it easy for developers, both front-end and back-end, to work with, leading to quicker development and visualization of data.

I advise others to understand the fundamentals of databases and how they store data. They should start with online videos to grasp the ecosystem, focusing on concepts like data storage. The document-oriented structure with binary objects is crucial for individuals with a programming background.

Several limitations related to querying certain documents can be challenging. They express concerns about the lookup process, where we sometimes need to fetch a large amount of data simultaneously. Additionally, there are limitations regarding the size of documents, which may require restructuring or storing data.

I rate it an eight out of ten.

We use this solution for database verification purposes. Typically, we integrate other analytics tools with the solution, like databases and other tools.

The Dynamic Application is a valuable feature.

The analytics needs improvement.

I have been using MongoDB for a couple of years. 

Hundreds of users use the solution at present. 

The initial setup is straightforward.

Overall, I would rate the solution an eight out of ten. 

We use MongoDB mainly for data visualization and filtering purposes.

MongoDB's most valuable feature is data visualization.

They could provide more documentation and examples for adding pipeline stages. There could be a feature where commands made in MongoDB could be easily copied and shared in their original format. This functionality would enable seamless transition and compatibility between platforms like Linux and mobile devices, reducing the need for complex filters or Citrix-based solutions.

We have been using MongoDB for five months.

I rate the platform's stability a nine out of ten.

My department has around 50 MongoDB users.

It is a cloud-based version and is simple to deploy.

We evaluated OracleDB and MongoDB. We decided to work with MongoDB as its interface is easier to understand and more universal. It offers ease of integration and simpler configurations compared to OracleDB. It also provides all the essential functionality.

I rate MongoDB a nine out of ten.

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.

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.

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.

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 primarily use the solution for web applications.

In our company we decided to invest in the knowledge of an alternative technology to SQL. MongoDB seemed like an obvious choice together with other leading technologies.Furthermore, it is a product that can be intuitive to use unless you come from years of SQL

It has quite good web analytics. It is pretty stable. There is more in-depth management of the data.

It's a NoSQL/Document DB and has some peculiarity related to the data schema but it's also good as a general-purpose DB.

The replication works very well and is in the box. 

In clusters, there is the choice to have horizontal scaling, which improves performance on a huge amount of data.

The aggregation framework is very powerful when elaborating on data. 

It has good high availability.

It's an essential DB. 

It has very good performance for queries.

It is free to use if you choose the community version.

It is stable and reliable.

You can easily scale the solution.

It's quite a good DB that is very strong on a lot of features. 

It is a product that works very well. I don't see a lot of areas that need improvement. 

I've used the solution for five to six years. I've used it for a while now. 

I'd rate the stability nine or ten out of ten. There are no bugs or glitches. It doesn't crash or freeze.

I'd rate the scalability nine or ten out of ten. It allows for horizontal scaling, which is quite useful when dealing with big data.

We have about ten people using the solution at this time. One-third of the company ends up using the solution.

We may increase usage. It depends on the business needs. However, in Italy, I have noted MongoDB is expanding.

The technical support is very good but is available only for the enterprise version. 

When I've used other DBs I found them to be inferior.

We have used also Atlas (MongoDB solution for Cloud), and MongoDB has developed a useful framework with lots of new features that are not included in MongoDB's on-premise version. If you choose a cloud DB, it's great if you are looking for a lot of innovative features. 

Many clients use SQL DBs and many are moving over to MongoDB.

The initial setup was pretty straightforward to set up. Compared to other SQL DBs, SQL databases are very complex. MongoDB is ready to go, and you need less operational knowledge. 

I do not invest in MongoDB. However, many customers can save money by leveraging the MongoDB community version. 

The community version is free. The enterprise version is reasonable as MongoDB wants to expand and outpace also SQL DBs. 

I am not using the latest version of the solution. 

Do not think of this solution as a SQL database. Consider your use case and set it up accordingly.

I'd rate the solution ten out of ten. It's the best database on the market.