MongoDB Reviews

We use MongoDB for handling document-based databases, specifically for sending unemployment forms using Form IO. 

In remote areas where technology is not widely available, the forms can be scanned and uploaded, and they are stored as key-value pairs in the MongoDB NoSQL database.

MongoDB allows us to store unstructured data with flexibility. It has enhanced our ability to file unemployment processes for individuals who cannot access the system to create a claimant ID.

The most valuable features of MongoDB include the flexible schema for storing data, its replication capabilities with high availability through a replica set setup, and horizontal scalability using sharding.

There was a need for integrating relational database capabilities, however, MongoDB has introduced a relational converter that allows conversion between SQL and NoSQL.

We migrated to MongoDB back in 2019 during the COVID period.

MongoDB scales horizontally using sharding, which is efficient and enhances performance by reducing load and increasing speed.

We used a traditional SQL database before moving to MongoDB. My exposure to MongoDB's ability to handle unstructured data was compelling.

The initial setup was easy, largely due to my preparation for certification and the support from site reliability engineers and architects.

The implementation was assisted by a site reliability engineer, and I prepared a playbook for guidance.

I am not entirely aware of the exact pricing details, however, MongoDB is a fairly valued product.

MongoDB is an excellent choice for those seeking flexibility in storing unstructured data. Its replication, high availability, and horizontal scaling through sharding make it very valuable. Understanding JSON and gaining certification can greatly aid in leveraging MongoDB effectively.

I'd rate the solution ten 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 done a variety of things with MongoDB that started with the adoption of this solution at one company. I was involved in setting up the cluster and then the monitoring, alerting, and backup process. Once all of the set up was complete, I was involved in writing some of the components that were responsible for fetching data from MongoDB.

We are now responsible for running the platform, so whoever wants to run MongoDB comes to us and we explain how we can deploy the cluster for their applications. At this point, we build a cluster in the servers under a UNIX account. The number of nodes in the cluster depends on the requirements of the application side.

Some of the use cases we have configured MongoDB for are desk-tooling and a payment card profiling project. We are currently working on a data exchange platform. We also have a couple of use cases in the pipeline for potential MongoDB clients who also need the MongoDB Ops Manager.

The most valuable feature is that we don't need a schema to store the data.

The security is very good. Cybersecurity, authentication, authorization, and server certifications are all valuable features. We can define security rules at the database level or the cluster level to grant or deny access to particular users.

This is a highly available architecture. If you are using a three-node cluster and one of these goes down then either of the secondary nodes will become a priority to eliminate downtime from the application's perspective.

The documentation for MongoDB is not very good and should be improved. Some of the documents are referring to legacy versions. MongoDB 4.2 has been released, but there are training documents and other documentation that still refers to versions 3.6 and 3.4, which is not good. They should definitely update the documentation as new software is released.

Data encryption is possible using third-party tools but they should have their own encryption capability built-in to this solution.

Information about upcoming and recently released features should be made available so that we are aware of the latest features, and how we can manage the issues that will accompany them.

I have been working with MongoDB for the last three years.

We have not had any issues with stability.

We have a support portal where we can log tickets and fix issues. We contact them directly and we can set up a call whenever we need help from them.

For some issues, I would rate technical support a nine out of ten, or a ten out of ten. However, at other times, I would rate them a seven out of ten. It depends on who is dealing with the ticket. There are times where they respond to tickets very quickly and things get resolved in a timely manner. At other times, it takes ages to resolve the problem.

We did not use a different NoSQL solution prior to MongoDB.

We continue to use Microsoft SQL Server for other types of database implementations that require SQL, which I also have expertise in.

The initial setup is not very complex. We used the MongoDB resources to understand how to set it up on a Linux server, and after that, we prepared our own document that explains how to install it. Now it is quite straightforward, although if you are going with a more granular level of configuration, such as enabling other parameters on the cluster, then it would be different. I would say that set up would be a little more difficult, but not much. It's very simple using the MongoDB Ops Manager.

We offer three types of services on the MongoDB platform. First is the ODS service, second is the MongoDB SQL, and third is MongoDB standalone. For standalone, we are providing services on the tenant. With respect to shared services, we have the infrastructure but we have to set up their database on the shared servers. This will be useful for some use cases. The standalone configuration takes approximately 15 to 20 days to set up. It is sometimes less but it takes the time to create and configure the UNIX account because we have a third-party dependency for that.

The ODS solution will be better for enterprise data such as those involving payments, accounts, and customers. 

MongoDB is a solution that I can recommend because we have realized good benefits from it. We are in the process of setting up the ODS project, which should help the organization from a cost perspective. Then we will be moving the mainframe data to ODS, and we can use the MongoDB API to fetch data from there and provide real-time solutions to the customer.

At this time, I cannot judge the benefit of MongoDB in isolation, but as time goes on, perhaps by the end of the year, I will have a better idea.

I would rate this solution an eight out of ten.

Our primary use case is mainly for web applications.

The document-based style is valuable as it allows for easy addition of sub-documents, unlike a relational database. It adds flexibility and facilitates data management. The geospatial index feature is also useful for dealing with latitude and longitude data.

The free tools, like MongoDB Compass, could be enhanced. This is especially relevant for the IDEs or similar tools.

I have been using MongoDB for about ten years or so. I am not certain of the exact years, however, it has been since almost version three.

MongoDB is quite stable. I haven't encountered any application-breaking problems with it. It handles backups well and doesn't have significant disadvantages.

I rate the scalability of MongoDB as eight out of ten. It is used for very large databases and is very useful, although we don't use it much.

MongoDB has tech support and customer support, however, I have not personally contacted them.

Positive

I have evaluated RDBMS, MySQL, and Azure SQL previously. MongoDB's advantage is its flexibility as a document database, though it doesn't mean it's better than other databases. It depends on the implementation.

The initial setup is relatively easy, similar to setting up MySQL or other databases.

I am not sure about the return on investment as I don't have knowledge regarding the purchase and related aspects.

MongoDB is free of charge. that said, there is also a paid version. We use both free and paid versions.

I evaluated RDBMS, MySQL, and Azure SQL.

To start with MongoDB, I recommend reading their documentation, as it is quite sufficient.

I'd rate the solution nine out of ten.

I am basically a developer and also a freelancer. I take up a lot of freelance projects for which I use MongoDB. I use it for the database system on my website.

The tool provides some free packages for freshers, which is very good because a lot of beginners or students don't want to spend too much money on it. The tool is also user-friendly. I don't make any connections a lot of the time if I use MongoDB in my project.

I previously encountered some issues with the tool, which included downtime issues. Sometimes, the tool goes down temporarily. There are some stability issues in the product.

There are some problems with the tool's website, and it can get laggy, but otherwise, it is pretty good.

I have been using MongoDB for more than a year. I am just a user of the tool.

The tool works most of the time, but it may go down at times. Stability-wise, I rate the solution a seven out of ten.

The tool's scalability is pretty good. Scalability-wise, I rate the solution an eight out of ten.

MongoDB is pretty popular, and we have a lot of documents and support available for it. The community is pretty big for it. I never faced any problems.

I have a little experience with SQL, but. I have major experience with MongoDB because it is well compared to other tools.

The product's initial setup phase is easy.

The product's deployment phase can be done quickly. In a few minutes, we can create a database, get the APIs, and use it without any issues.

The pricing is normal. Price-wise, the product is not too much expensive.

Though the replication features in the product are pretty good, I don't use them a lot.

I definitely recommend the tool to other people. A lot of startups can use it, and some people can already use it. If some students want to do some project, they can use the tool as its pricing is reasonable. The support and stability of the tool are also okay.

I rate the tool an eight out of ten.

I work with multiple personal applications, and for that, I use MongoDB and SQL Servers. Depending on the use cases, I choose MongoDB, as it is not a heavy application. Usually, I use MongoDB for attachment sections because RDBMS is heavy for attachment software. I also use it for assessments. Sometimes, I store data for a time-series database, such as stock market data, which I analyze using MongoDB.

Feature-wise, I like how MongoDB stores attachments because it allows me to store the results of the attachment and pull them up whenever needed instead of having to generate them every time. I can save those results as PDFs and other formats rather than just saving the data and then having to regenerate it. This approach enables me to analyze the attachments and research existing data, making it easier to retrieve information when needed. Overall, MongoDB has helped manage and analyze attachment data.

I cannot comment on how to improve the database since I am not an expert in that field. It is important to note that MongoDB has limitations since it can only be used for specific use cases. For example, for master data, I would want to pick keys using an RDBMS, but for attachments, I would choose MongoDB. Other than that, I am more familiar with RDBMS databases.

I have experience with MongoDB for three to four years and am an end-user of the solution.

It is a stable solution. Stability-wise, I rate the solution a nine out of ten.

It is a highly scalable solution. In fact, a friend of mine who works as a stock market analyst and operates using one of the popular websites in India also uses MongoDB for his work and finds it very efficient. Scalability-wise, I would rate the solution a nine out of ten. From my end, only four to five people use the solution, but from my organization's perspective, around 500 users are utilizing it.

We used to handle technical support ourselves, as the tool was easy to handle, and we didn't need any special assistance. Although we never had to interact with technical support, I would rate it a nine out of ten.

Positive

Previously, I used RDBMS but found it a bit slower. That's why I switched to MongoDB for analytics purposes. I had also tried using MySQL long back before using ClickHouse, but after that, I didn't use MySQL again. While using MySQL earlier, I faced some performance issues while writing a lot of entries. So I shifted to MongoDB, which has been working well for me. Although MySQL is an open-source solution, its performance was lagging. I also tried using Oracle, but it was a costlier option.

The initial setup of MongoDB was easy for me, and I found the community support to be very helpful. I rate the initial setup process a nine out of ten. The deployment process was also quick and only took a day or less. All that was required was to install the solution, which didn't take much time. I deployed the solution on my own, and it doesn't require any maintenance. As a friend and I only use it, it is for personal use only.

I chose MongoDB because it is cost-effective compared to Oracle, which can be expensive. In addition, MongoDB has good performance and has not caused any issues while working with it. It has been a good choice for me.

I recommend MongoDB because I haven't experienced any issues with it so far. Therefore, I would definitely recommend it to others. I wouldn't give the tool a ten out of ten since there is always room for improvement. I rate the overall solution a nine out of ten.

It stores historical data with ease. For example, if you are a healthcare member, then you will have multiple records of visits to the doctors. To store such data in Oracle Database, you have to create many records. You might also have duplication problems because your records are going in again and again, because of which the data warehouse and the maintenance cost will be huge. MongoDB is comparatively lightweight. It is a JSON extract. Once you define a schema and extract it, you can push all the relationships in any way you want. It is easier to define and get different types of transactions into MongoDB. It is also easier to set it up as compared to other solutions.

MongoDB is a NoSQL database, which means it is a document DB in which you can store documents that you created in BSON. It is pretty fast in response. It is faster than relational databases because it does not define any primary keys, secondary keys, tertiary keys, and all those kinds of things.

A normal Oracle or database tester will take some time to gear up to MongoDB because the way of writing queries is different in MongoDB. There should be some kind of midway where a person who is coming from an Oracle background can write a query and get a response by using something like a select * statement or other such things. There should be some way for MongoDB to interpret these commands rather than making a person learn MongoDB commands and writing them. I struggled while writing these MongoDB commands. I had not seen such queries before. It was pretty difficult to get them. This is one of the areas where it would help from the improvement standpoint.

It is stable.

It is scalable.

I haven't called them ever. I haven't seen any issues, so I would say it's pretty good.

I don't know, but I have heard from people who procure it that it is much cheaper than Oracle.

It is a good tool. You should give it a try. It has a very good and different perspective of looking at how data can be stored in a database and restored from a database because it is not like a straight query or record. The data is just in files. It does whatever a database should do.

I would rate MongoDB a nine out of ten.

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.