MongoDB Atlas Reviews

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 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.

There are many scenarios that MongoDB can fit into, like where there is a fluid schema and no transaction management.

This solution is deployed on a cloud and AWS is the provider.

It's flexible. We don't need to have a solid upstream availability failover, and everything is seamless in Atlas. They do all the replication, and all that is probably happening behind the scenes. The pricing isn't that high compared to any of the IBM products.

The biggest challenge we all have is an application layer level. One node is sitting in the APAC region, another node is sitting in the US and UK region. The seamless replication has to be lightning fast, but we haven't tested the scalability yet.

There's no straight answer for any of the database providers in that particular space. We don't have a failover, but when it comes to the RPA recovery point objective and RTO, we have to test it.

Atlas should think about a provision in the form of a commitment. You can ask for a longer commitment. Database is one thing. Once I build an application, if it goes to production, it's going to be there for the next 10 years minimum. In that way, somebody's giving you a commitment for five years, so you can give them a huge discount. If somebody's giving a two year commitment, you can give them a better discount. 

I've been using this solution for about six months. 

It's stable.

I haven't used this solution long enough to gauge the scalability. 

We haven't had any issues so far.

It's straightforward and seamless. Setting up takes about 35 minutes, but it could be as little as 20 minutes. We never had a concern with installation. Maybe when you're doing a data migration, that could be a different story altogether.

In development, we have about 15 users. The number of users could go up to 100,000 people because it's an application that we're building. We're building the system for 100,000 concurrent users.

We have the possibility of growing every year on year, probably 30%. We are going to test it to see if we can host multiple tenants in this single DB and if it will be scalable.

We pay for the license on a monthly basis. It's not cheap or expensive. For smaller companies, it's definitely expensive.

I would rate this solution 8 out of 10.

I would recommend this solution to those who want to start using it.

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 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.

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. 

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.

We use it for hosting data on the cloud.

It enables us to get work done quickly and get to our data. It benefits us by providing performance.

• As a user, it is very easy to use. There is nothing complicated.
• We can write queries and go through it very quickly; our queries are quicker with it. 
• Many tools are there. Other companies are providing many tools for getting to your MongoDB.

The import and export process needs improvement, i.e., getting in and out. Moving data from other databases into MongoDB, along with indexing, was challenging. However, it has been improving.

I would like them to make the product easier to use.

We are happy right now with stability unless something goes wrong down the line. In that case, you have to bite the bullet.

In terms of workloads, we put 60 to 80 percent on it.

So far, so good. However, we have had issues with our VPC, and how we have stored on S3 and our instances that we have with MongoDB. We are learning as we are building more capacity.

Our environment is utility customers, which is millions of meters, and each one has their own instance. We obtain that data for every 15 minutes in a big city environment, which is why performance is very important.

The technical support is good. We have received very good feedback.

The integration and configuration were pretty easy. We loved it. Otherwise, we would have changed databases.

We have definitely seen ROI.

The purchasing process through the AWS Marketplace was very good.

I was involved later on in the evaluation process when we were looking to import and export data out of MongoDB. We looked at MySQL, but we wanted to be on the cloud instead of managing our data on MySQL.

I would recommend it. It is better than the legacy databases, and it is very good with the cloud.

We integrated it with TestRail and JIRA. Everything is on cloud. It integrates well, and we are happy with it.