MongoDB Atlas Reviews

The product is simple to use and enterprise-ready. It is also open-source. 

I rate the product's stability a nine out of ten. 

The tool's deployment is easy. We used Amazon EC2 Containers to deploy it. 

MongoDB Atlas is a convenient database that you need to start using. I rate it a nine 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.

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.

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.

We use the solution to build applications online.

I would like to have better performance for user experience with the solution.

I have been using the solution for one and a half years.

The initial setup is straightforward.

I give the solution an eight out of ten.

We have eight to ten people using the solution in our organization.

I recommend the solution. There are no problems with MongoDB Atlas

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.

We use it for all of our temporary data, anything which is not warehoused.

It works with AWS Lamda and EC2.

It is nice because our developers create tables whenever they need to sync data. There are allocations nor DBAs. It is just use it as you need it.

• Autoscaling
• No overhead
• No maintenance

We had some bad trainers when we first came onboard and would rate them fairly low. They did not seem staffed properly to fulfill the training services that they offered.

It is very stable. It has been running without issues.

We have about 2000 customers a day.

The pricing is good. We originally chose it over DynamoDB because of the pricing.

We also looked at DynamoDB from Amazon. However, it didn't have the features that we wanted from MongoDB.

We chose MongoDB based on its pricing and features.

I have been happy with the service. Everything is good. Though, nothing stands out to me as exceptional. 

I would encourage someone to look at DynamoDB, even though I am fine with MongoDB. If you are in a fully integrated into the AWS environment, you might want to stick with Amazon Web Services rather than a third-party.

We use it as a service, so we don't configure anything.

Any business types where we need instructional data.

In a previous company where I worked, we were able to use MongoDB as a pure data storage using the block storage mechanism for our clients.

You can start quickly on projects which allow you to store many things.

I would like a more comprehensive dashboard. The UI can be difficult to understand.

Going forward, we would like to have pure AWS Cloud (native) storage instead regular storage on the AWS integration side.

The stability is very good.

In my previous company, we had a lot of data coming in every day, and the product remained stable.

We have been able to scale from gigabytes to terabytes easily.

I have never used technical support.

The integration and configuration of MongoDB in the AWS environment is quite good.

In my previous company, the product allowed use to build a database in a highly regulated environment with the ability to get distributed storage. We used MongoDB as a distributed storage to set up this environment for a critical business application with millions of dollars.

My advice is make developers understand NoSQL databases. For people coming from the SQL world, this is a new way to develop applications and that is the point to focus on. In the NoSQL world, MongoDB is a product that has a good awareness and has proven to be very good.

Our clients also evaluate Cassandra or other key value storage vendors. Its depends on what they want to do exactly. MongoDB is somewhere in the middle between pure key value and something like Cassandra, which is designed for bigger deployments.

MongoDB is fortunately well known now in the development community and has a good framework for languages, which is why our clients chose the product.

We are always integrating this product with our business applications because it is a database. Without our applications, the product doesn't make sense. The integration is quite straightforward, because of the consistences within MongoDB, you can find where to connect it.

I have used both the AWS and the on-premise versions. The AWS integration allows you to go faster in terms of deployment and the tooling in the cloud also allows you to go faster.