MongoDB Atlas Reviews & Product Details

By using the mongodb atlas cloud it is very easy to scale up on one click and it is very easy to integrate with application and for the day to day usage it is very easy .It is customer support and user interface is soo easy to manage. Review collected by and hosted on G2.com.

In dont like about the altas is that that pricing comes expensive as a data and cluster. cold start issue for the paused cluster. Review collected by and hosted on G2.com.

Flexibility, Ease of use and efficiency as well database connection and interaction while development phase. Review collected by and hosted on G2.com.

For the NoSQL databases, it's fine; I didn't feel that anything was wrong. Review collected by and hosted on G2.com.

simplicity, ease of use, scaling, sharding, data management Review collected by and hosted on G2.com.

Sometimes the database clusters take time while loading the data Review collected by and hosted on G2.com.

It good as it store different types of data structures, different types of documents as it as good scalability and has good performance. Review collected by and hosted on G2.com.

It doesn't support multi document ACID and contains high memory usage which has data inconsistencies sometimes. Review collected by and hosted on G2.com.

I have nothing good to say about MongoDB Atlas. Review collected by and hosted on G2.com.

My story with Mongo began when I started a new software position, and they had a legacy version of their software product using Atlas.

Compared to our other infrastructure bills, Mongo was significantly higher for the amount of compute and storage we used ($3K per month). This is a managed service, so you would expect to pay a premium. Ok, sure, but then I expect great functionality, performance, and support.

The main problem began with Mongo when we needed to delete some data because they tie the CPU and memory tiers to storage size, so we were overpaying. Our application would run fine off an M10 dedicated cluster (the smallest tier), but it had automatically scaled to an M50 because of storage. This is already a bit disappointing because they are forcing customers to pay for more compute and memory than they need.

So we started deleting some data, but then we ran into problems. The data deletion process was really slow and also slowed our entire cluster down, causing lag and performance issues for our end users. But hang on, this makes no sense because we are paying for more CPU and RAM than we need, so why would we have this issue?

It took us three months to delete 500GB of data. In the meantime, our bill remained the same because you can't claim the space back without compacting the database. Ok, fine. So we ran compact(), but we only freed ~100GB on the secondary clusters.

Support gave us a script to run that can see how much storage can be freed.

In the end, we had to activate an expensive additional support plan costing us $500 USD per month to get support to run a re-sync command. This should have taken their support people 10 minutes, but instead, they mucked us around going back and forth on the ticket, taking three weeks to resolve.

A year later, we needed to delete some more data. We spent another five months deleting 800GB of data. Then we ran compact() and freed 300GB. Where is our other 500GB? We contacted some humans at Mongo, who really couldn't do much other than suggest we get funding to cover the $500 support for one month. Yes, we got the $500 credit, but when I went to reactivate support, it was going to charge us for three months for one month because Mongo retroactively bills you for three months when you reactivate. Wow, we started in a bad place, now I'm beyond frustrated; this is daylight robbery.

To this day, I am still fighting to reclaim some storage, but at this point, I'm going to recommend to our CEO that our dev team put some effort into moving away completely from Mongo.

I also need to mention that Mongo recommended we use their online archive features, but when we crunched the numbers, it was still quite expensive, and we would have to do significant work to make our application work between the regular clusters and online archive. So it was significantly more logical to just put the data in AWS S3, then delete it in Mongo.

If I can summarize my experience with Mongo, and I acknowledge mine is probably quite different to most, here it is:

Overpriced for the performance you get

Sneaky billing model where they tie CPU and memory to storage

Terrible and expensive support

Sneaky extra charges on reactivating support

Bad support escalation solutions - they couldn't just turn on free 'support'

Poor database performance

Slow delete operations

Ecosystem lock-in

Forced upgrades - no LTS releases

Let me sum it up this way: if your compact() command does not free up the space that is available on your cluster, then provide the customer with free support to do so.

I hate dealing with Mongo. Nothing is simple, everything is expensive, and the performance sucks.

If you are considering using Mongo, find something else. Even if you have to take a bit more time to learn AWS Dynamo, S3, or Aurora, you should do it; you will save time and money in the long run.

Mongo, you deserve this negative review. I have given you plenty of opportunities to resolve things and have escalated issues, but you just don't care.

We wanted to move away from Mongo before; now I can't get rid of it fast enough. Review collected by and hosted on G2.com.

The mongodb GUI is very good to view the collection and manage to the databases Review collected by and hosted on G2.com.

The GUI of we cannot see the user details Review collected by and hosted on G2.com.

Ease of use and great UI. Enterprise-ready features. Security, Review collected by and hosted on G2.com.

The alerting system must be better. The integration with other monitoring systems should be seamless. Review collected by and hosted on G2.com.

Highly efficient and scalable database service. Mongodb Atlas is a highly effective databse web service in terms of features and integrations. With just a few clicks you can browse through your data collections. It provides us with a very smooth interface and a lot of integration tools also Atlas offers us a wide range of monitoring and deployment tools. You can connect your codebase to mongodb and can easily fetch, upload and perform other CRUD operations within seconds. Review collected by and hosted on G2.com.

Although mongodb Atlas it a great database web interface, it has some a steep learning curve for non database users. Review collected by and hosted on G2.com.

It is effortless to use. The documentation and tutorial are on point and help users get started even if they have a basic idea about cloud database deployment. The interface is very good and very intuitive. It also provides a CLI which users like me prefer over the UI. One more feature I like is the fantastic backup facility they have. I can continue from the point I left even if my system shuts down in between. It has customizable features that help me organize my projects in different orgs according to my wishes. It also has support for Kubernetes and AWS which are additional good features. The storage compression is good and does not take up much space. Review collected by and hosted on G2.com.

Clusters shared with other users do not seem to work as efficiently as single-user clusters. There is a time lag and collaboration features are not that effective. I cannot use it if I have too much querying. Review collected by and hosted on G2.com.

MongoDB Atlas is fantastic! It is a scalable, adaptable NoSQL database that gives you the freedom to store data as you want, scales easily, and is secure everywhere. It's also just expensive for what you use. Well worth looking into! Review collected by and hosted on G2.com.

Although MongoDB Atlas excels in terms of scalability and versatility, it is not without flaws. Despite its strength, the document model may require some familiarity with relational databases. Furthermore, compared to certain SQL solutions, its pay-per-use model might grow expensive for high workloads. Review collected by and hosted on G2.com.