We may use it as an application database. The application stores the data as documents in the database, which is a preference for our company because it’s a Document DB and a NoSQL database, which are preferred over traditional relational databases.

MongoDB has wrapped up the whole development lifecycle. MongoDB has multiple built-in tools such as MongoDB Shell, Compass, and other tools. It helps the developers to use that specific tool efficiently. Users do not have to worry about finding the tools and then installing and using that specific tool to communicate with their database cluster. MongoDB has a built-in option using MongoDB Shell or Compass for that purpose.

So, it has positively impacted the development speed and productivity.

There are many valuable features, but scalability stands out. It can scale across zones. You can define multiple nodes. They have also partnered with AWS, offering great service with multiple features, including built-in backup, all under the same roof, without the need for external tools.

So, the scalability feature supported our data growth overall. The growth of the database depends on the application side. The database aids in scaling when the application requires more storage.

It’s configured to scale automatically across zones and regions, ensuring that performance doesn’t degrade even when scaling down.

The scalability aspect is quite difficult to implement. It should be much easier for the end user. You cannot use less than two nodes; you have to use at least two nodes, and they categorize their nodes, like m5, m10, and m20, according to their resource practices, which are also a bit expensive.

The end-user has to learn a bit about it. MongoDB has great content on its site. They call it MongoDB University. They actually have great content for that. Anyone can learn it, but one has to study it before diving into it or starting to use it.

I have been using MongoDB Atlas for almost three years.

The scalability is good. In my team, almost the whole development team is using it. So, there are around five end users.

I contacted customer service and support for multiple purposes while configuring. The support is quite efficient, and the guidance is quite good. Initially, when I was working on it, I had to communicate with the support team.

So, I had a good experience with the support.

The initial setup is not too difficult but can be somewhat tricky.

It is tricky mainly in terms of configuration, especially if it's not internet-accessible, configuring it to stay within the same data center while allowing developers access without network barriers.

It is worth my money at the end of the day.

The pricing is not that expensive, but it can be, especially when we have deployed it across multiple zones.

If you want to go with NoSQL, I would suggest using MongoDB.

If you are saving documents and prefer AWS services, AWS also has their DynamoDB for that purpose. I would suggest using AWS service if all of your services are already on AWS.

Overall, I would rate it a seven out of ten.

We restore our golden data from various sources and then push it to MongoDB. We make our CDP from MongoDB, which serves as a device-centric system.

There is a built-in feature called Autoscaling In MongoDB Atlas. This feature automatically adjusts the configuration of MongoDB based on the volume of users we ingest daily. Autoscaling dynamically scales the resources to accommodate the load when our data flow increases.

The real-time data visible within MongoDB Atlas is not accurate. If they can improve the UI that monitors real-time data. It's more impressive and more attractive. It could be more user-friendly.

I have been using MongoDB Atlas for two years.

The product is pretty stable.

The solution is scalable. Autoscaling supports it.

50 users are using this solution

Whenever we have doubts during configuration, we reach out for assistance. We must upgrade certain parameters in our MongoDB setup, prompting us to contact their support team. They resolve such issues within four to five hours.

The initial setup is not very complex. It is easy to use. It's easy to deploy on MongoDB. We push from GitHub. From there, we specify where the data is restored in MongoDB. We continue to connect. It puts the data and delivers it to Argo City.

The product has a yearly subscription.

We have assigned DevOps for security.

The overview and monitoring part will address this issue, and then we will use it to observe any increasing traffic on our website. We also monitor the rising number of connections due to this traffic. It's quite easy to oversee everything in one place. However, the UI isn't particularly user-friendly.

I've also used it in my previous company and found it handy and easy to configure, including easy capabilities.

We are establishing SLAs that are directly tied to MongoDB. All are interconnected with MongoDB. If MongoDB experiences downtime or RAM or CPU usage spikes significantly, users may encounter difficulties logging in. This reliance on MongoDB can pose challenges for user accessibility, particularly when considering the conferencing tools we use.

Overall, I rate the solution an eight 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.

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.

It's good for performance and stability if you need a non-SQL database to store data.

We use it as a database for some of our microservices. We use it as a database for a few of our microservices.

The stability and performance are great. The high availability feature is great.

Moreover, I am happy with the automated backup and restore functionality.

In the past, MongoDB offered more features for free, but now it's quite limited. The free version is limited, and you need to pay extra to fully utilize it.

The pricing could be improved.

I have experience with this solution. I've been with this product for a couple of years.

It is a stable solution. I would rate the stability a nine out of ten.

It is a scalable product, but only if you use the paid features. And if you enable sharded cluster functionality, it scales very well.

The initial setup is very straightforward.

The ease of setting up and maintaining your database clusters with MongoDB depends on the features you need. If you only need basic functionality, setup can be simple. But for additional features like reliability and backups, it might require a more complex configuration.

We did it in-house.

Overall, I would rate the solution a nine out of ten. I would recommend using this product.

If you need a no-SQL database, then MongoDB is a good choice.

The product is simple to use and enterprise-ready. It is also open-source.

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

The tool's deployment is easy. We used Amazon EC2 Containers to deploy it.

MongoDB Atlas is a convenient database that you need to start using. I rate it a nine out of ten.

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 use MongoDB Atlas to store the data of our users.

The product allows us to easily set up and store large amounts of unstructured data.

The product's data aggregation feature needs to work faster.

We have been using MongoDB Atlas for one year.

I rate the product's stability a nine out of ten. It is a good feature that is rarely seen in other relational databases.

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

The initial setup process is easy.

It is an open-source platform.

If you have unstructured data in large amounts, MongoDB Atlas is a good product to opt for. It distributes the data on servers and gives quick access to it.

I rate it a nine out of ten.

We use MongoDB Atlas to manage transactions and tenant payments for our application.

The product provides quick transaction service, high availability, and efficient scalability features.

The product's file storage documentation needs improvement.

We have been using MongoDB Atlas for five years.

It is a stable platform. I rate its stability a nine out of ten.

I rate the product's scalability a nine out of ten.

We are using MySQL at the same time.

The initial setup requires knowledge of Linux systems. It takes ten to thirty minutes to complete, depending on the bandwidth of the server. It requires a team of three technicians to execute the process.

MongoDB Atlas is a wonderful product. It is one of the top database platforms. I recommend it to companies planning to use the standard transaction maintenance.

I rate it a nine out of ten.

I use MongoDB Atlas to take care of my company's clients who are in industries like healthcare systems, finance, and other such areas.

The solution is valuable since it works as an unstructured database.

I would like the solution to offer more integration capabilities since it is an area where the solution lacks.

I have been using MongoDB Atlas for a few months.

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

It is a scalable solution.

Around 30,000 to 40,000 of my company's customers use MongoDB Atlas.

I was not involved much with the technical support offered by MongoDB.

The initial setup of MongoDB Atlas is straightforward unless you don't have to deal with any database-related stuff.

I completed the setup phase of the solution in a week since I have a background in handling databases.

For the deployment phase of the solution to be successful, one needs to have a bit of cloud-based knowledge.

I did not get into the solution's licensing costs since that is taken care of by the customers who want to use the product.

I recommend the solution to those who plan to use it.

I rate the overall solution an eight out of ten.