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.

In my SaaS role, MongoDB Atlas helped me meet compliance standards by keeping tenant and customer data in separate databases. I improved performance by setting up Atlas clusters in each region. In a high-restriction context, data replication between regions ensured smooth failover without constant snapshots. For added security, I even took data snapshots to another cloud. Choosing MongoDB Atlas depends on your specific SLA and disaster recovery needs.

The most beneficial MongoDB features for our workload are the ability to scale up and down using automatic sharding and clustering. This is crucial for handling diverse requirements and integrations with different configurations. The flexibility to support various deployments, whether on AWS, Azure, or GCP, by easily adding additional clusters, has been another significant advantage.

There is room for improvement in the cost of certain features like encryption. The web console isn't very intuitive, especially for large data. The new feature, Cube, for BI needs better documentation, and more workshops or videos would be helpful for users and developers. Additionally, real-time performance monitoring in MongoDB Atlas needs improvement.

I have been working with MongoDB Atlas for about two months, but my company has been using it for a couple of years.

MongoDB is quite stable.

The technical support is very good. I would rate it as an eight out of ten.

Positive

I have worked with MySQL and PostgreSQL. MongoDB stands out for managing JSON and document types most efficiently. While other databases support JSON fields, MongoDB offers the best solution for handling JSON data.

The deployment was quite straightforward and it only took about half a day. 
Maintenance is generally manageable with MongoDB, but it becomes challenging when facing issues or disasters. The profiler and logs are not very user-friendly which makes it harder to identify and resolve problems quickly.

The ROI with MongoDB Atlas depends on how well you manage your data and throughput. It is crucial to understand your data and use their tools effectively. Mismanagement can lead to higher costs, especially with scaling, so careful monitoring is essential.

I don't have any concerns about MongoDB Atlas pricing and licensing.

MongoDB's default encryption provides a baseline for data protection. The flexibility to let customers manage their encryption keys enhances security.

MongoDB Atlas supports our organization's implementation of microservices architecture by seamlessly fitting into our domain-driven design. While we primarily use domain-driven design rather than microservices, MongoDB Atlas offers flexibility and scalability to meet various requirements. It easily accommodates diverse data structures and events related to our customers, allowing for efficient and straightforward implementation.

Overall, I would rate MongoDB Atlas as a seven out of ten.

My advice to new users is to design your schema thoughtfully, considering MongoDB's document limitations. Utilize profiling and set up alerts for scaling issues. Understand how to query efficiently and focus on proper indexing for improved performance.

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.

Positive

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 manage services and keep them running. The business analyzes the social media data with machine learning, and that data is stored in MongoDB.

Administering the solution is easy.

The administration is not very interactive. Most of the time, you don't need to interact with the database, just create a user and indexes. It's not very friendly for developers.

Based on its own habitat, it's not ACID compliant. If it had an ACID compliant option, it would be more useful for database administration.

I have been using this solution for almost three years.

It's a stable solution.

I think there are two kinds of support. One of them is local. If there is any trouble, we open the ticket with a local vendor. If they can't solve those problems, they escalate the problem to the level three engineers at MongoDB.

I would rate their technical support 4 out of 5.

I have also used Microsoft SQL databases. There's a distinction between SQL and MongoDB because one of them is based on the schema first. The other is not schema, not permanent, because of ACID compliant databases. The transaction is very important at the SQL, MYSQL, and Postgre databases, so if any transaction fails, it has to roll back because of the schema at most of ACID compliant databases. 

There are 35 million customers that consume those databases, like a POC system. Lots of transactions passing through the system are based on Microsoft SQL. Only semi-structured data – like a document based system like Twitter and social media data – is based on MongoDB.

There are two kinds of setup. One of those setups is sharding, and there is replication. The other setup is hybrid. It's not hard to implement those systems.

Setup is easy. There are only a few commands that you have to execute. First of all, the design is a very important part of it. If you design it based on the best practices, it's easy.

As a database administrator, all those things come around as ready to run. You only need to log in to the server and implement SQL, Mongo, and MySQL databases to implement. It takes only half a day to implement those.

We had a lot of documentation. Most of the time, we couldn't expand those rules, but it's easy to implement. 

We have almost 11 people on the database team.

Comparing the price between the MongoDB and Microsoft SQL Server, we are using the enterprise edition of Microsoft SQL Server, which is more expensive than MongoDB.

I would rate the price of MongoDB 4 out of 5.

I would rate this solution 10 out of 10.

It's a solid product. A lot of issues have been resolved. It's very sustainable, and it takes minimal effort to solve a problem. It's very easy to deploy.

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 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.