MongoDB Atlas Reviews

We use it to power a software-as-a-service cloud solution to book meeting rooms, parking spaces, and workspaces. We have multiple clients using this solution. A Node.js backend is also being used along with Mongoose, and it is running on Cloud Run. Then there is a VPC connection to MongoDB Atlas.

The most valuable feature is that it's all web-based. So one can browse collections just from the web. MongoDB Atlas is easily accessible, quick to understand, and quick to learn. People who have never used CLI can hop into the web interface and browse the database.

When I edit a document from the web-based Explorer, a lot of clicking is involved, like changing data type manually from a drop-down. It would be super nice if I could just edit the document in a JSON format. The JSON-based document editor should have a multi-language feature. Also, it would be great if there was a connector for Google Looker Studio.

I have been using it for three years.

The interface could be more reliable. It is not a stable product because sometimes we see the explorer being down or unable to log data and the interface turning to the five hundred server error. However, it's ninety-five percent stable. I don't always trust it, but most of the time, I do.

It scales well. I can only hope that it would be possible to configure and that it could scale down quicker. Now it takes twenty-four hours to scale down.

We have 15 developers who regularly use the solution.

The experience with the first-level support was a bit annoying as they took a lot of hours to figure out the issue, even though it was clear what needed to be corrected. But the professional support team on the paid support plan gave a clear and detailed response.

We've used SQL in the past. While building our product, and our architecture, MongoDB was very simple and a better choice. We chose to switch to MongoDB Atlas specifically because we did not want to manage our deployment database on our own. We chose to use MongoDB Atlas because it was the best choice in the market for managing MongoDB databases. It has a proper interface, and it's easy to get started. Its ability to run on Google Cloud Platform is one of the key sectors as the rest of our efforts run on it.

The initial setup was super easy. It took 15 minutes to setup.

I advise others to use the solution. I would tell others to use the serverless option, but not for people near Frankfurt, as the serverless interface is unavailable for Google Cloud in Frankfurt.

I would give it an eight out of ten as it's easy to use and quick to start.

We use MongoDB Atlas for all of our payment transaction processing.

The are many advantages that we have experienced while utilizing the MongoDB Atlas. By working with this tool, our teams have been able to progress quickly without the need to involve any internal provisioning departments. This empowers application developers to independently manage the scaling up and down of the database clusters, allowing the database to be treated as an integral component of the application itself. As a result, this has significantly streamlined the development process and increased efficiency.

MongoDB Atlas is a platform as a service and it has proven to be particularly valuable due to its self-managing nature. This has allowed us to minimize the amount of time and effort required to manage it, as it effectively manages itself. Additionally, it is a complete solution when looking at its features.

A few areas that we have noticed as being problematic with the MongoDB Atlas include user access to the platform. Currently, it is difficult to restrict and control what actions a user can perform within the solution, which poses a challenge from an internal auditing perspective.

I have been using MongoDB Atlas for approximately five years.

My overall impression of the stability of the MongoDB Atlas is incredibly positive. From our experience, it has proven to be highly reliable and efficient in its operation. The fact that it has built-in features such as auto-scaling and automatic updates enhances its stability even further. Additionally, its performance management capabilities, particularly in regard to indexing, are truly impressive. This level of stability has allowed us to focus on other tasks, as we do not have to frequently return to make adjustments or resolve issues with the database.

The scalability of the solution is amazing. We plan to increase our usage.

There have been instances when we have needed to reach out to the technical support team for assistance. In order to ensure the highest level of security and connectivity, we have implemented measures, such as utilizing Google Private Connect and engaging with MongoDB Atlas. These actions were necessary to effectively resolve any questions or issues that arose.

The technical support team at MongoDB Atlas is incredibly friendly and accommodating. They make you feel like more than just a client and their expertise in technology is exceptional. Unfortunately, there has been some fluctuation within the team and it is rare that we are able to speak with the same person on multiple occasions. However, despite this, they consistently go above and beyond in providing assistance and resolving any issues.

I rate the support from MongoDB Atlas a seven out of ten.

Neutral

I have not used another solution similar to MongoDB Atlas.

The initial setup process for this specific item is incredibly straightforward and simple, requiring only a few clicks of buttons to initiate its deployment. This makes it incredibly user-friendly, as even individuals with limited technical knowledge or expertise are able to complete the setup with ease. Its design is foolproof, which is a testament to its efficiency and accessibility.

The deployment process consisted of several important steps. Firstly, we logged into the MongoDB Atlas database to access the cluster that we desired to deploy. We specified the size we wanted and then initiated the deployment process. After completion, the solution was up and running and accessible through the internet.

The deployment takes only a few minutes.

The solution was internally managed and deployed.

The return on investment comes from the engineering experience. That's been a good return on investment.

The price of MongoDB Atlas is highly affordable. 

When comparing the costs of managing the data internally versus utilizing an external solution, it is significantly more cost-effective to choose the latter option. The external solution saves on the resources and expertise needed to manage the data in-house, making it a more economical choice.

The standard license that we have is a basic agreement that covers most of the typical usage requirements. However, we understand that each client has different needs and therefore, we are open to negotiating discounts and custom usage agreements. As far as fees go, we do not have any additional charges other than the standard license. On rare occasions, they might offer training or consultancy services which might incur additional charges, but these are typically communicated beforehand and agreed upon.

Before making the ultimate decision to select MongoDB Atlas as our database platform, we thoroughly evaluated several other options that were available to us. We had access to the Cassandra database system and the Relational Database Service (RDS), as well as our existing traditional database systems such as Oracle. All of these options were carefully examined and evaluated to ensure that we were making the best decision for our needs.

The choice to utilize the MongoDB Atlas was made due to the complexity and richness of the data sets that needed to be stored. The team evaluated other options, including Amazon's DynamoDB, but found that MongoDB Atlas was seamless and was a better fit for their needs. The benefits of using MongoDB Atlas include the ability to handle complex data without the constraint of a strict schema. There have not been any drawbacks or negative experiences in using this solution, as the team has consistently found it to be effective and efficient.

I use the solution daily.

My advice to others is for them to use the solution and stop doing everything themselves.

I rate MongoDB Atlas a nine out of ten.

We're developing a product using multi-tenant architecture, but we don't have any predefined structure, so we need to use MongoDB Atlas to support predefined architecture.

Being schemaless is what I like best about MongoDB Atlas.

An area for improvement in MongoDB Atlas is that it does not support individual or personal database backup, though it supports cloud cluster backup.

I want a query feature added to MongoDB Atlas, or if it's available, improve on it. My team needs manual coding for the pipelines, for example, creating and executing pipelines. If the query feature of MongoDB Atlas has some improvement, then the process for pipeline creation and execution would be better.

I've been using MongoDB Atlas for around three years.

MongoDB Atlas is a stable solution. A product related to it, the MongoDB Atlas Data Lake, on the other hand, could be more stable.

My company contacted the MongoDB Atlas Australian support team once, and I'm rating the team eight out of ten.

Positive

We decided to go with MongoDB Atlas because you also get MongoDB Realm, a product that lets you sync data with mobile devices.

MongoDB Atlas has an easy setup.

I didn't deploy the solution because another senior took care of the deployment.

I'm not familiar with the cost of MongoDB Atlas.

I'm using MongoDB Atlas version 4.2.

The solution is deployed on the MongoDB cloud.

Around four people, mainly developers and techs, use MongoDB Atlas within the company.

I recommend MongoDB Atlas to others because of the support my company gets, apart from the product being schemaless. MongoDB Atlas also has other features, and you can take advantage of MongoDB Realm, so it's like getting more than one product.

My rating for MongoDB Atlas is eight out of ten.

My company is a MongoDB Atlas customer.

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.

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 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.

I have used MongoDB Atlas for my personal side projects as a database, and I have also used it as an infrastructure-as-code (IAC). In my apps, I have used the API to manage and create new databases programmatically. At my workplace, we use MongoDB Atlas for database management, access management, and configuration using Microsoft.

The key feature of MongoDB Atlas that has been helpful for us is the ease of deploying new databases. As a SaaS product, we don't need to worry about the infrastructure for on-premises servers or maintaining them. Additionally, MongoDB Atlas allows us to connect to our cloud, whether it's Azure, GCP, or AWS. This means we can manage these resources within our own cloud environment, change security rules, and integrate with other cloud resources as needed.

There are more than one hundred users in my organization.

I find the cluster demonstration and APIs to be the most valuable features of MongoDB Atlas. The APIs allow me to programmatically make changes to the environment. Additionally, the interface is user-friendly and easy to navigate. Another feature that I find useful is the separation of projects, which allows for different projects to have their own settings.

One improvement that I would like to see is a feature to export changes made in the environment, such as creating a new user. MongoDB Atlas should provide a way to export this action programmatically, so that we can easily integrate it with our IAC tools and deploy it afterwards.

I have been working with MongoDB for around six years now, and have been using MongoDB Atlas since it was launched. I believe it's been about two years since I started using Atlas, but I can't recall the exact time.

It is a very stable solution.

MongoDB Atlas is scalable and it offers several features for a DB as a service.

We have used Azure SQL in the past, but it's not the main use in projects in the organization. We have also used MongoDB Atlas for their project, and Oracle DB is used in the organization as well.

The initial setup was very easy. We didn’t need any expert to set up the solution.

For my personal projects, I mainly use the UI interface of MongoDB Atlas, as well as the APIs. I write code that connects to the APIs and makes changes to the environment, such as creating new databases and managing security settings. In an enterprise setting, we typically have an administrator who uses the user interface to manage the environment, so there's not as much need for a specific deployment process.

There is some ROI because we don't need to have a separate operations team to maintain servers physically. MongoDB Atlas eliminates the need to worry about physical things like energy and space, as they are managed by the cloud provider.

It has a fair price.

I prefer GCP because it's free and has great features related to artificial intelligence and the network is also very good. However, Azure has the best interface that is easy to use and deploy. It has ERM templates, which are JSON templates used to define resources that can be deployed, making it easier to work with. In contrast, GCP lacks such templates and some APIs are not easy to use.

I've had a very positive experience using MongoDB Atlas so far. It's easy to use, and scalable, and the cloud-based option is very convenient. Overall, I would definitely recommend it to others looking for a database solution.

I would advise learning some SQL concepts to use MongoDB Atlas correctly. MongoDB Atlas is a cloud-based platform that provides a managed database service for MongoDB, a NoSQL database. Additionally, it is important to have network knowledge, specifically for administrators.

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