MongoDB Atlas Reviews

In my SaaS role, MongoDB Atlas helped me meet compliance standards by keeping tenant and customer data in separate databases. I improved performance by setting up Atlas clusters in each region. In a high-restriction context, data replication between regions ensured smooth failover without constant snapshots. For added security, I even took data snapshots to another cloud. Choosing MongoDB Atlas depends on your specific SLA and disaster recovery needs.

The most beneficial MongoDB features for our workload are the ability to scale up and down using automatic sharding and clustering. This is crucial for handling diverse requirements and integrations with different configurations. The flexibility to support various deployments, whether on AWS, Azure, or GCP, by easily adding additional clusters, has been another significant advantage.

There is room for improvement in the cost of certain features like encryption. The web console isn't very intuitive, especially for large data. The new feature, Cube, for BI needs better documentation, and more workshops or videos would be helpful for users and developers. Additionally, real-time performance monitoring in MongoDB Atlas needs improvement.

I have been working with MongoDB Atlas for about two months, but my company has been using it for a couple of years.

MongoDB is quite stable.

The technical support is very good. I would rate it as an eight out of ten.

I have worked with MySQL and PostgreSQL. MongoDB stands out for managing JSON and document types most efficiently. While other databases support JSON fields, MongoDB offers the best solution for handling JSON data.

The deployment was quite straightforward and it only took about half a day. 
Maintenance is generally manageable with MongoDB, but it becomes challenging when facing issues or disasters. The profiler and logs are not very user-friendly which makes it harder to identify and resolve problems quickly.

The ROI with MongoDB Atlas depends on how well you manage your data and throughput. It is crucial to understand your data and use their tools effectively. Mismanagement can lead to higher costs, especially with scaling, so careful monitoring is essential.

I don't have any concerns about MongoDB Atlas pricing and licensing.

MongoDB's default encryption provides a baseline for data protection. The flexibility to let customers manage their encryption keys enhances security.

MongoDB Atlas supports our organization's implementation of microservices architecture by seamlessly fitting into our domain-driven design. While we primarily use domain-driven design rather than microservices, MongoDB Atlas offers flexibility and scalability to meet various requirements. It easily accommodates diverse data structures and events related to our customers, allowing for efficient and straightforward implementation.

Overall, I would rate MongoDB Atlas as a seven out of ten.

My advice to new users is to design your schema thoughtfully, considering MongoDB's document limitations. Utilize profiling and set up alerts for scaling issues. Understand how to query efficiently and focus on proper indexing for improved performance.

I manage services and keep them running. The business analyzes the social media data with machine learning, and that data is stored in MongoDB.

Administering the solution is easy.

The administration is not very interactive. Most of the time, you don't need to interact with the database, just create a user and indexes. It's not very friendly for developers.

Based on its own habitat, it's not ACID compliant. If it had an ACID compliant option, it would be more useful for database administration.

I have been using this solution for almost three years.

It's a stable solution.

I think there are two kinds of support. One of them is local. If there is any trouble, we open the ticket with a local vendor. If they can't solve those problems, they escalate the problem to the level three engineers at MongoDB.

I would rate their technical support 4 out of 5.

I have also used Microsoft SQL databases. There's a distinction between SQL and MongoDB because one of them is based on the schema first. The other is not schema, not permanent, because of ACID compliant databases. The transaction is very important at the SQL, MYSQL, and Postgre databases, so if any transaction fails, it has to roll back because of the schema at most of ACID compliant databases. 

There are 35 million customers that consume those databases, like a POC system. Lots of transactions passing through the system are based on Microsoft SQL. Only semi-structured data – like a document based system like Twitter and social media data – is based on MongoDB.

There are two kinds of setup. One of those setups is sharding, and there is replication. The other setup is hybrid. It's not hard to implement those systems.

Setup is easy. There are only a few commands that you have to execute. First of all, the design is a very important part of it. If you design it based on the best practices, it's easy.

As a database administrator, all those things come around as ready to run. You only need to log in to the server and implement SQL, Mongo, and MySQL databases to implement. It takes only half a day to implement those.

We had a lot of documentation. Most of the time, we couldn't expand those rules, but it's easy to implement. 

We have almost 11 people on the database team.

Comparing the price between the MongoDB and Microsoft SQL Server, we are using the enterprise edition of Microsoft SQL Server, which is more expensive than MongoDB.

I would rate the price of MongoDB 4 out of 5.

I would rate this solution 10 out of 10.

It's a solid product. A lot of issues have been resolved. It's very sustainable, and it takes minimal effort to solve a problem. It's very easy to deploy.

We store all our data in MongoDB. Our frontend application is .NET, our backend is .NET, and the database is MongoDB.

We have two products running on MongoDB: a financial expense management solution and a sustainability product.

It can store data as a flat file, similar to a file system. It's called Atlas GridFS and it works very well.

MongoDB is a very good database. The Community Edition is free, which is cost-effective for development.

The API support is excellent for integration.

From an improvement standpoint, MongoDB can improve security.

There are some challenges from a security point of view. Since the file can be easily accessed, there should be more security features. The data should be encrypted in some form to prevent unauthorized access.

We've been using MongoDB for three to four years.

I would rate the stability a nine out of ten.

We haven't seen high volumes of data yet. Our solution is for expense management, not a full ERP solution. So far, the system has been stable with the current number of users.

It should be scalable and easily work with other databases like SQL or Oracle. We shouldn't have trouble converting the data.

I would rate the scalability a nine out of ten. Some security features are still under development.

MongoDB isn't for our internal users; it's for our customers. Depending on the organization, it can go up to ten thousand or even a hundred thousand users. We have a lot of customers using our applications built on MongoDB.

We are a young company, only five years old. We recently started this product, but we know that around a hundred people are using it in one of our products for web and mobile.

We have a very strong internal technical team that manages everything. We haven't needed any support from MongoDB because our team is proficient in using it.

My team only recommended MongoDB. We haven't worked with other databases for our current projects. I have worked with SQL Server and Oracle in the past as an SAP consultant, but those were for ERP systems, not application development.

MongoDB's setup is very easy. We plan to only use MongoDB for our future database needs.

It works very well with the .NET and Angular platforms due to the flat file support. So, we went with that option.

The main benefits include cost savings and speed. The application runs fast, and accessing data is quick.

ROI is very good. 

It's very easy to manage for our technical data analysts.

Overall, I would rate the solution a nine out of ten. I recommend using MongoDB because it's free for development, scalable, and user-friendly for connecting with frontend and backend technologies like Angular and .NET.

We primarily utilize MongoDB Atlas for tasks such as IoT integration. Additionally, it serves as a general-purpose database that aggregates analytics data before transferring it to a data lake. Its versatility allows for various applications, providing flexibility and ensuring the availability of essential data across different systems. While it is used in diverse contexts, many use it for IoT-related initiatives.

We prefer MongoDB Atlas over SQL because most of the data generated with IoT devices is unstructured. This gives you flexibility; you don't have to define specific schemas all the time, and sometimes, the structure of the object varies.

It improves data management along the same lines. MongoDB Atlas supports structured data with IoT projects.

MongoDB Atlas was explicitly designed to support IoT applications. Many databases offer features tailored for IoT use cases.

One area for enhancement is containerization. They could explore ways to facilitate deploying MongoDB containers within the platform.

I have been using MongoDB Atlas for five years.

I rate the solution’s stability a nine out of ten.

Two people use this solution because they work with sensors and other variations of IoT.
I rate the solution’s scalability a nine out of ten.

The tool provides a forum where users can engage with experts. These experts offer assistance tailored to your specific needs, whether you're focused on product-centric queries or diving deep into particular use cases. Ultimately, the support you receive depends on your requirements and the extent of your experience with the platform.

The initial setup of MongoDB Atlas is straightforward. The user-friendly UI guides you through the setup process seamlessly. It would be beneficial if they could maintain this simplicity across different operating systems. Additionally, if they can streamline the process to easily deploy with containers, it would greatly enhance user experience and make life easier.

MongoDB Atlas offers various options based on your needs. It can accommodate both, whether you require the enterprise version with advanced features or prefer to start with an open trial version.

Security is primarily organized around organizational principles, allowing you to customize and adjust each tool according to your specific security policies. I recommend the product. Every product serves a purpose as long as it addresses the right problem. MongoDB Atlas has proven particularly effective for applications such as analytics and IoT, making it a recommended choice for those use cases.

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

We use it in a cloud setup on Google Cloud Platform as part of a microservices-based cloud solution. These microservices communicate with messages, and one use case for MongoDB is storing specific messages we're interested in.

MongoDB has supported our organization's need for scalable and flexible data storage.

We use it internally, where different teams manage different microservices. Sometimes, internal incidents arise, requiring teams to dedicate personnel to resolve and communicate with other teams. 

With MongoDB, other teams can now access some of our data and investigate issues on their own, freeing up personnel for other tasks.

Moreover, this solution simplifies real-time data analytics or application development for our business.

It simplifies things by automating previously manual tasks. It acts as a self-service portal for our team, reducing manual work and enabling automation.

We're happy with the performance, maintenance, and especially the ease of use within Google Cloud.

Given our microservices architecture, it's like a large puzzle, and MongoDB feels like it fills the gaps we were facing. So, the global clusters feature has enhanced our application performance and user experience.

It helps us optimize team performance, which is valuable.

The initial configuration could be a bit easier.

I have been using this solution for a couple of years. 

We've experienced some issues, but most MongoDB issues are resolved quickly. The issues we face are mainly with other systems.

So, it is a stable solution. 

It is a scalable solution because we use quite a lot of data, and it handles it well.

It's a microservice solution, so each microservice runs on several pods, maybe eight. Each pod uses MongoDB and makes its own connections, so multiply by eight, maybe 100, so roughly a thousand users.

These are internal users, so we're fine with the current number.

MongoDB offers free support online, and they seem to be doing a good job overall.

We have used other databases as well, including Google Cloud, for the past two years on our current project. My company policy guides such decisions. Overall, the company is happy with MongoDB.

The setup is automated through our partner using Terraform for provisioning, not just for MongoDB but for our whole infrastructure. We manage daily deployments using TerraForm, and MongoDB setup on Google Cloud is very smooth.

The deployment is very quick. For example, microservices using MongoDB start very quickly, possibly within a minute.

We haven't had major issues with deployment or configuration. Maybe initial configuration fine-tuning for performance can be time-consuming, but the initial effort pays off later with reduced maintenance needs. 

Expertise in automation and deployment processes is helpful and worth learning within the team.

We do it in-house. It's integrated with Google Cloud, GitHub, and GitLab actions. Everything is cloud-based and easy to work with. It's been continually improving over the years.

We don't use external consultants, as we have in-house expertise. It's a 100% cloud solution.

We don't have engineers dedicated to maintenance. It's part of our continuous integration and delivery environment, so there's not much manual intervention needed. Issues usually arise when deploying incorrectly and rolling back, but deployment itself is straightforward.

In some teams, companies, and projects, there might be two to three people dedicated to everything, which is a lot. If these skills to analyze productivity or cost saving can be automated, these people can teach others and do more valuable work. It's all win-win.

The price is cheap enough. It is comparable and has average pricing. We have a long-term license.

The pricing is acceptable for enterprise tier.

We haven't faced any major issues so I would rate this solution a nine out of ten.

In this project, it's more integrated than previous ones. The level of integration, automation, and evolution is impressive when used well. It's flawless, straightforward, and hassle-free.

MongoDB Atlas is a schema-less database.

MongoDB Atlas is very easy to use and user-friendly, and you get what you're paying for. MongoDB Atlas is very easy to use when you are familiar with MongoDB and how to write query functions. I would give the solution a nine out of ten for usability.

MongoDB Atlas should improve its user experience by providing better explanations or a wizard for people working with its UI. The solution should include a query builder that will help people who aren't developers get data.

I have been using MongoDB Atlas for two years.

MongoDB Atlas is a stable solution.

MongoDB Atlas is a scalable solution. Around ten people were working with the solution in my organization.

The solution's initial setup is straightforward.

MongoDB Atlas provides good value for money. MongoDB Atlas is not expensive, and since it's a cloud-based solution, you pay by usage.

MongoDB Atlas is a cloud-based solution. The solution's installation, setting up, and integration are relatively easy. MongoDB Atlas provides the functionalities it promises.

Users should focus on the technical design and figure out how they want the data, what data scheme they're aiming for, how to build properly, and how to design data properly. For everything else, they provide you with enough tools to understand what you're doing pretty much by yourself.

Overall, I rate MongoDB Atlas a nine out of ten.

We work with millions of rows of data and we use MongoDB Atlas for data.

The most valuable feature of MongoDB Atlas is it's seamless when working with a lot of different systems. Additionally, it is able to adjust the data based on the data being received.

We have a data repository that is floating and MongoDB Atlas allows many data from different sources without the need to convert it.

The solution allows for encryption, quick processing, self-manages, and indexes on the fly.

The price of the solution should be reduced.

I have used MongoDB Atlas within the last 12 months.

The solution is incredibly stable. The solution keeps a copy of the data in different locations around the world. It is up 24 hours a day seven days a week.

The scalability of the solution could be made simpler, it can be technical. It can be difficult to create applications and proof of concepts. 

The support is fine. You rarely connect with the support because of a problem. They are called more often if find out how to do some operations.

The initial setup of MongoDB Atlas is simple. You create the infrastructure and the solution read the data and organizes it.

For large projects, MongoDB Atlas has proven an ROI.

The price of MongoDB Atlas is highly expensive to use and maintain. They are taking advantage of the users with such a high price.

I would advise others to use the free component of MongoDB Atlas to see if the solution can be maintained in their organization.

I rate MongoDB Atlas a nine out of ten.

Apart from meeting all our high-performance database needs, the major use of MongoDB Atlas is for migrating most of the queries toward the UI part. With the Data API feature, we can now create database queries directly from the UI, which we  build in React and Angular. After creating the queries from the UI, we hit the Data API, and the results are obtained directly, making it the best feature we have come across lately.

The most valuable feature of MongoDB Atlas is that it's on the cloud, so you don't need to set up all your servers. It has the latest features like MongoDB Atlas Data Lake, Data APIs, and high-performance MongoDB on the cloud. It also allows us to visualize data through charts. So, the charts are visible on MongoDB Atlas. In my projects, I found users to be the most useful feature of the solution. We deployed MongoDB Atlas for around 500 users and gave them different authorized roles and permissions, allowing us to create an updated database this year.

I believe MongoDB Atlas has room for improvement in terms of providing more convenient UIs for data manipulation. At present, we are required to create an HTTP proxy after the database and then use the UI to communicate with the database via that proxy. If MongoDB Atlas could offer UI features to create tables and add or update records from them, it would eliminate the need for UI development. For instance, if we have a table or collection of orders and products, and MongoDB has charts, then MongoDB Atlas could offer some tables to create tables, create orders, create products, update orders, update products, and link orders and products. So, we are basically expecting a UI to change the database.

For the additional features, I think giving the UI or the user interface to create tables or something similar would help simplify creating orders and products for a layman with zero technical knowledge.

I have used MongoDB Atlas quite a lot. I think it's been more than one and a half to two years since we, as a company, have been using it in our projects. Also, I have used it for personal and professional projects.

I think that my company is a customer of MongoDB Atlas.

MongoDB Atlas is a database that is quite fast, stable, and reliable.

In my company, quite a lot of people are using MongoDB Atlas, with the majority of them relying on it. To put a number on it, I think more than 300 people are currently using MongoDB Atlas. Also, it is a scalable product.

We have a team that takes care of technical support for MongoDB Atlas. I'm not sure if any complaints have been reported to them, but personally, I haven't had any issues that required me to raise a complaint.

We decided to migrate from the old Legacy SQL databases and try out new things. MongoDB Atlas provided functionalities beyond just being a database, and we have been very satisfied with it.

MongoDB Atlas can be deployed on all three major cloud providers, which include AWS, Google Cloud, and Azure. When creating an Atlas instance, one can choose which cloud provider to use.

Setting up MongoDB Atlas is a breeze. The setup process is very easy.

The time it takes to deploy MongoDB Atlas can vary from person to person, depending on their satisfaction. However, depending on the size, it usually takes around one and a half to four or five minutes. But I think the deployment time can be reduced to just 15 to 30 seconds. That would make the process even better.

I'm more of a technical person and don't take care of the cost. The finance team takes care of it. But I have seen the cost, and it was pretty cheap. The cost is in cents for the millions of requests the solution handles. I think that the solution is definitely worth the money.

If you look at it technically, it depends on individual requirements. MongoDB Atlas is certainly scalable, but when compared to Legacy SQL databases, they are actually less scalable. However, if your system doesn't need to be scalable at a global level and you only need the solution for just two or three countries, or you only have around 10 to 20 million users, then MongoDB Atlas is a great option to consider because of the additional functionalities it provides above and beyond just being a database.

The UI is not currently designed in a manner to make it possible for a non-technical person or a layman to update the database easily. This is the first point to consider. Secondly, MongoDB Atlas is essentially a cloud-based database, so it should offer some provision for performing the same tasks on local computers. I believe that MongoDB Atlas will implement these improvements in the near future, so it won't take much time. Owing to the aforementioned reasons, I rate this solution an eight out of ten.