MongoDB Atlas Reviews

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. 

Positive

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.

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 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.

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 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.