MongoDB Atlas Reviews

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.  

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.

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.

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 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.

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.

I am impressed with the tool's integrations.

The tool's implementation should be made easier.

I have been working with the product for two years.

The solution is stable.

The tool is scalable. My company has more than 40 users for the solution.

We had mailed tech support whenever we encountered issues and they had responded to us.

The solution's deployment can be done in-house.

The tool is free since it's an open-source product.

I would rate the product an eight out of ten.