A typical use case for MongoDB Enterprise Advanced is mostly for the database, storing our data.
MongoDB Atlas for Government
MongoDB, IncExternal reviews
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Document data has streamlined prototyping and now supports secure cloud deployments
What is our primary use case?
What is most valuable?
I think the document-based approach is valuable. It's not SQL-based, so it's fairly easy to prototype. However, there is a con to that, which is that you don't have any migration. It's a double-edged sword.
We always use Redis for the in-memory storage engine with MongoDB Enterprise Advanced.
What needs improvement?
I don't really have a deep dive into it, but I see that MongoDB Enterprise Advanced has RAG and Vertex support. However, we really didn't use it because I think one thing also is that Prisma, the ORM that we use, doesn't have full support for MongoDB Enterprise Advanced. It really falls short of that because many developers are using Prisma instead of Mongoose or their underlying native drivers. I think one point is that their native drivers, or how you query data from their native tools, is just much more difficult.
For how long have I used the solution?
I have been using MongoDB Enterprise Advanced for over three years.
How are customer service and support?
I had technical support from MongoDB Enterprise Advanced over two years ago. I think they resolved it, but it was very long. We waited for a day or two.
How was the initial setup?
On Atlas, it can take about an hour, but on DigitalOcean, if I do it again, I'd say it's maybe two hours or so for setup.
I do it mostly alone for the installation.
What's my experience with pricing, setup cost, and licensing?
I think it depends on the provider. For example, on DigitalOcean, they have strict routing. You have to whitelist an IP address, or you risk getting DDoS. Then if you're going for the Atlas one that MongoDB Enterprise Advanced provides, it's fairly easy to set up.
What other advice do I have?
I use the cloud version of the product. MongoDB Enterprise Advanced is from MongoDB, though I also use DigitalOcean as a third-party provider.
Maybe it's all more about preferences. I think MongoDB Enterprise Advanced has weak support on the ORM side, particularly if you're using Prisma. I think mostly the focus now on the tools we have is PostgreSQL. MongoDB Enterprise Advanced is not really used that much on our side for production.
It's not really a weak point. It's more of a double-edged sword. If you like document-based management databases and you don't want any migrations, then you go to MongoDB Enterprise Advanced. If you want more secure databases, then you use SQL.
On the account management and the way you secure the connection strings, I have utilized advanced security features with MongoDB Enterprise Advanced.
I think it's very expensive on the Atlas enterprise side. But if you go to other providers of MongoDB Enterprise Advanced, such as DigitalOcean, it may be harder to set up, but they can save you money. My review rating for MongoDB Enterprise Advanced is 8 out of 10.
Reliable Hosting with Easy Scaling and Monitoring
What do you like best about the product?
I use MongoDB Atlas for hosting our MongoDB, and I appreciate its reliability; I've never had any problems with its uptime. I really like the tools it offers for scaling and performance monitoring, as they are easy to use with a nice user interface. It's great that new MongoDB versions are deployed as soon as they are released, allowing me to use new features without any delay. The initial setup was easy without any problems, which I really value.
What do you dislike about the product?
I think their alerting system may be a bit improved, for example so I can setup more granular alerts. For example, I can't set up composite rules (for example error rate of specific endpoint + CPU threshold, etc). Basically, it's limited in customization.
What problems is the product solving and how is that benefiting you?
MongoDB Atlas manages server setup, replication, autoscaling, and backup, saving me from managing these complex tasks.
Easy, Intuitive UI with Great Documentation
What do you like best about the product?
easy UI, very intuitive, good documentation
What do you dislike about the product?
there is nothing I dislike - customer support might respond faster
What problems is the product solving and how is that benefiting you?
Easy and very fast database setup for frontend projects
Atlas is our “set it and forget it” database layer
What do you like best about the product?
Automated scaling, backups, monitoring and performance alerts make it incredibly easy to maintain clusters without dedicating a team to infrastructure. Added to that, the UI is intuitive, queries run fast and features like Atlas Search, Charts and built-in security controls help ship features quickly.
What do you dislike about the product?
Some configuration options feel hidden behind tiers. Also, greater transparency around cost optimization or in-platform recommendations would make the experience even smoother.
What problems is the product solving and how is that benefiting you?
Atlas gives us a fully managed, highly scalable database platform so our team doesn’t have to manage uptime or deployments. Its ability to automatically handle all the operational tasks like backups, replication, sharding and monitoring, has allowed us to move faster, reduce operational overhead and maintain reliable uptime while scaling our applications.
Intuitive UI Simplifies Database Management
What do you like best about the product?
I appreciate MongoDB Atlas for making database management more user-friendly with its intuitive UI, which makes it more comfortable to work with compared to using only the terminal. The feature for managing MongoDB aggregations is particularly beneficial, allowing me to build queries from smaller parts efficiently and intuitively, making the process significantly easier than doing it manually. I highly value how MongoDB Atlas helps me work seamlessly with databases, especially when I am developing and need to check the state of my data. Its performance is fast, which I like, and it integrates well when I am working on the backend with Visual Studio Code. Overall, it's easy to set up if environment variables are configured correctly, making the whole process straightforward.
What do you dislike about the product?
I think it works great , I don't see anything to improve particularly
What problems is the product solving and how is that benefiting you?
I use MongoDB Atlas for database management due to its intuitive UI, making complex tasks like writing aggregations easier than using the terminal. It helps me efficiently query collections and manage data during development.
Have managed customer transaction data efficiently and supported high-demand workloads with reliable performance
What is our primary use case?
Our main use cases for MongoDB Enterprise Advanced involve customer-related data and transactions related data; all the customer-facing data will be there. For the project we are using it in telecom. All the customer-related transaction data, their plans, their telecom plans, their consumption, and all those details will be there.
We are using MongoDB Enterprise Advanced in the telecom domain, and we are using this in the customer-facing area. All the customer-related data both for transactions and point of sales data are stored here.
What is most valuable?
Advanced security features are helpful; our database access security is done through IAM, which is an AWS service, and that IAM is integrated with the security manager with single sign-on process, which is also an AWS service. It's a combination of all that. This was integrated with MongoDB Enterprise Advanced security perspective; that's how we are taking care of the access-related security.
We do use the in-memory storage engine as part of performance improvement; these are already tuned.
It improves the performance depending on the load. When the database receives numerous requests, it has to perform. Those threshold limits we come to know, and then automatically these memory enhancement advanced features are configured so that during high demand periods, memory automatically increases to cater to the incoming advanced requests and volume of requests.
We are using real-time analytics and monitoring in MongoDB Enterprise Advanced; it is integrated. The existing advanced feature is integrated with our business analytics interface. All the various business intelligence reports are generated from that.
What needs improvement?
The integration between data warehouse could be improved. Nowadays, a lot of data is getting generated, so certain ETL flexible scripts with backend database integrations would be an improvement I could see. I will not be able to clearly say there is currently a deficiency there.
All our DBs are integrated with a backend data warehouse, not necessarily AWS. When third-party data warehouses are integrated, we are seeing some ETL job performance issues. It is a one-off scenario so we have not thoroughly done any troubleshooting on that. It could be platform or third-party related issue. From the AWS standpoint, if robust integration and data warehouse integration specific tools are added in the advanced suite, that would definitely be helpful.
For how long have I used the solution?
I have been working with MongoDB Enterprise Advanced for almost more than three to four years.
What do I think about the stability of the solution?
It's pretty much stable; we have not faced any major challenges or difficulties with MongoDB Enterprise Advanced. It is basically transactional from the platform standpoint. Mostly from the product heavy search during those times, which presents capacity planning challenges only, but from the platform standpoint, we have not observed any specific technical issues.
It's pretty much stable; I haven't received any complaints regarding stability.
What do I think about the scalability of the solution?
MongoDB Enterprise Advanced is easy to scale.
How are customer service and support?
We did contact technical support for MongoDB Enterprise Advanced but it goes to a central team. We have received fairly good support whenever we reached out to the technical teams; they were prompt. Once in a while there was a bit of a delay in response but that depends on the technical issue. Overall, we are satisfied with the support.
How would you rate customer service and support?
Positive
How was the initial setup?
For MongoDB Enterprise Advanced, the initial setup is straightforward; it is not too complex. It is comfortable to implement.
What was our ROI?
I would say we see value in money and return on investment with MongoDB Enterprise Advanced.
What's my experience with pricing, setup cost, and licensing?
For a small company, the cost of MongoDB Enterprise Advanced is reasonable, but for heavy data usage, we see a little bit of cost pressure but it's acceptable. I will not be able to elaborate on that right now; we are satisfied with the pricing.
What other advice do I have?
It's good; for first-time users, if somebody is looking for a good guaranteed database for all structured and unstructured data, MongoDB Enterprise Advanced is the way to go. On a scale of one to ten, I rate this solution an eight.
Which deployment model are you using for this solution?
Hybrid Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
2+ Yrs of experience using mongodb atlas
What do you like best about the product?
Flexibility, Ease of use and efficiency as well database connection and interaction while development phase.
What do you dislike about the product?
For the NoSQL databases, it's fine; I didn't feel that anything was wrong.
What problems is the product solving and how is that benefiting you?
We have used this database for the IOT and edtech domain projects. The flexibility provided by the database is insane for the IOT application there is irrelevant and most of the unstructured data we are storing, its critical to manage in sql databases
A review by the user having experience of 2+ years
What do you like best about the product?
simplicity, ease of use, scaling, sharding, data management
What do you dislike about the product?
Sometimes the database clusters take time while loading the data
What problems is the product solving and how is that benefiting you?
We have used MongoDB Atlas to build IoT applications as well as payment systems.
Mongodb as the good flexibility, scalable to more data and performance , stores different data types
What do you like best about the product?
It good as it store different types of data structures, different types of documents as it as good scalability and has good performance.
What do you dislike about the product?
It doesn't support multi document ACID and contains high memory usage which has data inconsistencies sometimes.
What problems is the product solving and how is that benefiting you?
It helped me in doing the complex projects with the multiple documents and is flexible and has high availability and performance.
Open-source tool improves network monitoring and reporting efficiency
What is our primary use case?
What is most valuable?
MongoDB has definitely helped us improve our network monitoring and reporting dashboard, so I would say it has impacted our operations positively overall.
What needs improvement?
I'm not sure about the documentation or the knowledge bases available for MongoDB because I don't interact with it at that level, but I would say it's minimal and could be improved.
I am not experienced with MongoDB enough to know any pain points or areas they could improve.
Nothing else comes to mind at this time that could be improved.
For how long have I used the solution?
We deployed MongoDB about five years ago and it has been in operation since then.
What was my experience with deployment of the solution?
I was not a part of the initial setup or deployment of MongoDB.
One person was involved with the setup team, and it took just a few days to deploy it.
What do I think about the scalability of the solution?
Overall, on a scale of one to ten, I would rate MongoDB an eight; it's mostly because we're still running a monolithic environment on old hardware, so there are some limitations with read-write access.
Which solution did I use previously and why did I switch?
At this time, I'm only looking into Cisco or Linux or other solutions out of curiosity about possibly switching to it, but currently all that we use are LibreNMS and Splynx.
How was the initial setup?
From what I know, I would say the initial setup of MongoDB was pretty straightforward.
On LibreNMS, they have a template for setting up the environment that includes all the services, so MongoDB is just part of that template, meaning they weren't really too hands-on with setting up MongoDB itself.
What about the implementation team?
One person was involved with the setup team, and their job title was Network Operations Engineer.
Which other solutions did I evaluate?
I'm familiar with open-source databases such as MongoDB, and I don't think it's Grafana, but it's similar to Grafana, though I'm trying to think of what it's called.
I'm not entirely sure about the main differences between MongoDB and other open-source databases that I've used.
We haven't really delved too much into looking at comparisons for databases.
What other advice do I have?
MongoDB is not currently supporting our AI-driven projects nor do we use it along with AI at all.
I don't know how MongoDB's document-oriented model has benefited our management processes; that's beyond my expertise.
I don't have experience with QRadar or Auvik or similar products.
I'm familiar with some Linux tools, just things such as smokeping, which we use implemented in our LibreNMS environment.
I'm only an operator, so I don't actually spend a lot of time developing MongoDB, thus I'm not sure what the best features are.
I would rate MongoDB an eight out of ten.
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