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.

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.

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 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 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.

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 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 create a MongoDB database or clusters. Then, we connect it to the application in a normal simple way.

The dynamic structures are the most valuable. The SQL is fast but requires a different structure.

The speed when combining two documents is concerning. In SQL, there are Joins. You can define relationships between two tables and go for complicated structures, but you can't do that for MongoDB Atlas. You can have logical structures that do the same thing, but they are really slow compared to the Joins in SQL. Combining two separate documents within a database is not recommended because it affects performance. So if they can make it faster and more efficient, it would be amazing.

We have been using this solution for 15 months. I believe it is deployed on public cloud, AWS.

It is a stable solution. 

It is scalable, and they provide different options. We have about 20 people using the solution in our organization, and they are mostly developers.

The initial setup was straightforward.

I believe when it is deployed publicly, it is pretty cheap. But the costs are high if it is deployed on-premises or you're using a private database.

We decided to use MongoDB Atlas because we required some dynamic data structures. We never wanted to stick with a well-defined one. When there were questions about using well-defined ones, PostgreSQL turned out to be one of the choices, but we chose MongoDB Atlas.

I rate the solution an eight out of ten because it's a good product. It supports many functionalities, is easier to implement, and the only issue is speed. It also doesn't have a lot of features that could support Joins. So if they fix that, I could scale my rating as high as nine or ten. I would recommend the solution. It is very developer-friendly, and the learning curve is not that high.

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.