MongoDB Atlas Reviews

The primary use case was as a data layer of a low code/no code automation platform.

It provided us with independence from specific cloud provider services giving us a high level of consistency.

The auto-scaling feature is the most valuable aspect. It allows us to get an idea of the capacity without guessing or worrying about coming up short. 

We had some edge cases where auto-scale caused an issue where a node went offline at the same time and we had to deal with that. We had to reach out to support to resolve the issue.

There's a barrier entry in the support pricing from a sales point of view for a setup for a large number of small clusters so we had to fall back from purchasing the enterprise support for it.

The setup of integrations with cloud service providers as private connectivity and encryption can be improved.

I've been using the solution over a year.

Aside from the one-time issue we had with one cluster in our early stage, the solution shows to be highly reliable.

The platform is highly scalable and capable to adapt to the change in demand over time. We've constantly scaled up and down without issues.

We only had basic technical support. We did not have enterprise support. However, the regular support has been okay. They answered our questions within one or two days.

Positive

We went from MongoDB Enterprise to Atlas. We've used enterprise and community versions before going to Atlas.

In our case, we built an automation tool on top of it. We built our own Terraform module to standardize and automate the deployment to reach a level of consistency required and integrate with our deployment pipelines. 

Offloading part of the management tasks to the service provider highly reduced the management complexity.

We have witnessed an ROI while using Atlas. The cost was reduced greatly in comparison to our previous solution. There's also cost reduction spent on engineers in terms of maintenance.

The cost of the solution is fair. The cost savings are quite large compared to the enterprise solution. We've had a cost reduction moving to Atlas and have been able to do more than just running everything ourselves.

There is a cost for support that is based on the number of clusters, and that can be quite high for a large number of small clusters.

The platform itself we pay for usage.

The scalability is great. Now, you no longer need to guess how much you need. It makes it easy to grow the platform as you grow your product.

I'd rate the solution eight out of ten. 

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 use this solution for our NoSQL requirement. We store data, like JSON data, in MongoDB.

It's deployed on the cloud with AWS.

It's a good solution for NoSQL databases.

It would be better if there were more integration capabilities with other products.

I have been using this solution for six months.

It's stable.

It's scalable.

We would like to increase usage. Right now, we have 100 people using MongoDB, but in the future, our customers will be around one million when we open up the crypto exchange. 

Currently, we have a skilled DBA and don't need any consultancy. In the future, if there are more customers in all of our databases and the DBA is not enough to handle issues, then we will use a consultant for bottlenecks.

I have also used Oracle.

Setup is straightforward. Installing MongoDB takes only one day, but it will take you one week to customize MongoDB for all of the use cases.

For deployment and maintenance, we need two or three DBAs for both MongoDB and MariaDB.

We pay for a license.

I would rate this solution 9 out of 10.

I would recommend MongoDB Atlas for those who want to start using it. 

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 can be used to store data, migrate data from SQL to NoSQL, and collect data from websites.

Object-based data storing capability and managing non-structured data capability are the most valuable features of MongoDB Atlas.

MongoDB Atlas should add more APIs in their Terraform module because sometimes I find it difficult to find the resources in their Terraform model.

I have been using MongoDB Atlas for two to four years.

I rate MongoDB Atlas a nine out of ten for stability.

I rate MongoDB Atlas ten out of ten for scalability.

MongoDB Atlas’ initial setup was straightforward.

We use Terraform to deploy MongoDB Atlas. The deployment is easy if you have the code, and can be done within five minutes.

MongoDB Atlas has a good partnership with AWS, and there is no hassle in integrating the solution with any tool. I recommend users go ahead with MongoDB Atlas if they prefer to have NoSQL in their organization.

Overall, I rate MongoDB Atlas ten out of ten.

I'm no longer working for the company that uses MongoDB Atlas, and I didn't stay there long, but the search functionality of the solution was helpful. The cost reduction from using MongoDB Atlas has also been beneficial. The solution also supports pay-as-you-go, another benefit of MongoDB Atlas.

What I found most valuable in MongoDB Atlas is its Elasticsearch feature.

MongoDB Atlas would be better if it had facilities for data warehousing, data lake, or ETL jobs. It probably has this functionality for large data sets, but I've not read about it, and I'm not so sure.

It would also be great if it were easier to integrate MongoDB Atlas with AWS services. Native integration between MongoDB Atlas and AWS services would make the solution better.

In the next release of the solution, the company wants to receive better support from the MongoDB Atlas team.

I used MongoDB Atlas for eight to twelve months, but my last usage of the solution was six months ago.

MongoDB Atlas has high availability, so I have no complaints about its stability. When the database goes down, it results from huge queries or some malfunction in the operations, but the solution is usually stable.

Regarding scalability, if I'm running the free version of MongoDB Atlas, a tiny application, it's an eight out of ten. However, if I'm running an extensive application that requires some support, I'd rate the scalability of MongoDB Atlas as six out of ten.

I keep hearing from my previous team that the technical support for MongoDB Atlas has been slow on some queries or query executions.

You also have to pay for MongoDB Atlas support, and it's expensive. It would be great if support were cheaper because the team frequently interacts with technical support because of database failures, connection breaks, etc.

The technical support for MongoDB Atlas is not up to the mark, mainly because of the extra costs, so I'm rating that area three out of ten.

Negative

My company previously used Amazon DocumentDB, so I contacted the MongoDB Atlas team as I thought it would be better for the company to switch to MongoDB Atlas because it offered Elasticsearch, which would be helpful for the company's use case. Instead of setting up a separate Elasticsearch, my company can use the Elasticsearch functionality in MongoDB Atlas.

Another reason for switching to MongoDB Atlas is that its cost was significantly less than the cost of Amazon DocumentDB.

Amazon DocumentDB lacked some of the features you can find in MongoDB Atlas because it wasn't up-to-date with the latest MongoDB.

MongoDB also supported query execution, so it was better for the use case of my company.

It is pretty simple to set up MongoDB Atlas from scratch, and it's a good experience, but migrating from another solution to MongoDB Atlas is more complex. For example, the company was using Amazon DocumentDB and had to migrate from that solution to MongoDB Atlas. Because of the massive data, it took some time to migrate to MongoDB Atlas fully.

Deploying the solution required the support of the MongoDB Atlas team. Still, if you have one person with expertise on the infrastructure, for example, a DevOps person, that would suffice, primarily if your data volume isn't that big.

If it's a raw MongoDB Atlas setup, one person with basic skills can also handle the deployment by learning the ready-made setup process from YouTube. However, if you want to set the solution up with your EC2 instance sitting around in some VPC, you must do VPC pairing.

Connecting MongoDB Atlas with AWS Lambda on a VPC will be more challenging because it's outside the AWS native environment. Connecting the server to the MongoDB Atlas database would be a challenge. The deployment team would need various skill sets for challenging tasks, such as database migration, VPC pairing, etc.

An in-house team implemented MongoDB Atlas with a consultant from the MongoDB Atlas team.

I don't have many complaints about MongoDB Atlas, ROI-wise. It's just the support that's a little expensive, so on that side, there's not a very great ROI. However, from the database side, as MongoDB Atlas has many new features coming in, the ROI is okay.

MongoDB Atlas is more cost-effective than Amazon DocumentDB. It also has a pay-as-you-go pricing model.

Apart from the standard licensing cost, you must also pay to get MongoDB Atlas technical support, which is expensive.

MongoDB Atlas has different pricing models, so pricing is five out of ten for storing the data. The support is expensive, so that's three out of ten. For data updates, I'd give the price seven out of ten.

I have some experience with MongoDB Atlas.

I remember using version 4.2 of MongoDB Atlas.

I advise anyone planning to implement MongoDB Atlas to start small and get around the platform and documentation. Learn about the MongoDB Atlas fundamentals, such as VPC pairing, etc. If you want to scale the solution, review the documentation on that first, apart from learning the platform.

My rating for MongoDB Atlas is seven 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 the solution for our document databases, cloud databases, e-commerce databases, and invoices.

The solution has a very intuitive user interface. It is very simple to use.

The product should introduce database mapping between SQL queries and document queries.

The product does not have ORM.

I have been using the solution for the last eight years.

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

I rate the solution’s scalability a ten out of ten.

The initial setup was very straightforward.

Deployment can take anywhere between one month to six months.

The solution is fairly priced.

The product is cloud-based. Overall, I rate the product a nine out of ten.