Sold by: MongoDB, Inc
Vendor Insights
MongoDB Atlas for Government is a separate environment of MongoDB Atlas, dedicated to meeting the demanding security and privacy needs of the US Government. Easily deploy, operate, and scale MongoDB on AWS by letting Atlas take care of time-consuming administration tasks.
Sold by: MongoDB, Inc
Overview
MongoDB Atlas for Government has achieved FedRAMP Moderate Authorization and is a separate environment of MongoDB Atlas, dedicated to meeting the demanding security and privacy needs of the US Government.
It is a fully managed MongoDB service engineered and run by the same team that builds the database and MongoDB Atlas. It incorporates operational best practices we've learned from optimizing thousands of deployments across startups and the Fortune 100. Build on MongoDB Atlas for Government with confidence, knowing that you no longer need to worry about database management, setup, and configuration, software patching, monitoring, backups, or operating a reliable, distributed database cluster.
MongoDB Atlas for Government is available in AWS GovCloud and AWS US FedRAMP Moderate regions.MongoDB Atlas for Government for AWS Marketplace includes: 24,000 MongoDB Atlas for Government Credits valid for 12 months for USD 24,000. Credits are consumed based on the chosen cluster configuration, backup settings, and network transfer costs
MongoDB Atlas for Government Pro Support with 2 hr response time SLA. The MongoDB Atlas for Government Pro plan provides access to proactive, consultative support. The same team that builds the database helps you throughout your entire application lifecycle. You can ask MongoDB experts unlimited questions, 24 x 365, globally.
Highlights
- Highly available: Clusters are geo-distributed fault-tolerant and self-healing. Deploy across multiple regions (e.g.: spanning GovCloud east and west regions) for even better guarantees and local reads.
- Protect your data: Strong security defaults with authentication, network isolation, encryption, and role-based access controls keep your data protected.
- Build semantic search and AI-powered applications: Integrate the operational database and vector search in a single, unified, and fully managed developer data platform with a MongoDB native interface that leverages large language models (LLMs) through popular frameworks
Details
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Security credentials achieved
(3)
ISO27001
SOC2
FedRAMP
Financing for AWS Marketplace purchases
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MongoDB Atlas for Government
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Customer reviews
Joe S.
Overpriced, Poor performance and some of the worse support I have ever had to deal with
Reviewed on Dec 16, 2024
Review provided by G2
What do you like best about the product?
I have nothing good to say about MongoDB Atlas.
What do you dislike about the product?
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.
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.
What problems is the product solving and how is that benefiting you?
A simple managed database to get up and moving quickly as a developer.
Leave a comment0 comments
Sandip s.
MongoDB- Ease and portable
Reviewed on Jun 20, 2024
Review provided by G2
What do you like best about the product?
Portability, easy to fire up, and requires less resource
What do you dislike about the product?
So far nothing I have found that concerns me about mongo
What problems is the product solving and how is that benefiting you?
I use MongoDB to save embedding for my chat model
Arambhika S.
One of the best database platform
Reviewed on Apr 04, 2024
Review provided by G2
What do you like best about the product?
MongoDB's simplicity is amazing. You can store data how you like, amend it as per your preferences, and implement the changes as you want to.
What do you dislike about the product?
Only one thing, the collections are not updated automatically.
What problems is the product solving and how is that benefiting you?
It helps in making changes on the live projects. It helps in setting up our backends of our projects and we can fix the issues in the application on real time basis.
Noman S.
Using vector search feature for the products
Reviewed on Feb 11, 2024
Review provided by G2
What do you like best about the product?
It's scalability and incorporating latest trends in the product
What do you dislike about the product?
May be the cost. I think cost should be reduced
What problems is the product solving and how is that benefiting you?
We are hosting our product embedding/vectors in the vector index that is being used to find the most similar vectors quickly
Nilesh B.
Easy to use, flexible and secured.
Reviewed on Jan 22, 2024
Review provided by G2
What do you like best about the product?
It is NOSQL database which is easy to use and installation. It is secured and easily manageble. It is cost effective.
What do you dislike about the product?
The sources regarding this are very less according to other database. Althought it is easy to use but sometimes need some support.
What problems is the product solving and how is that benefiting you?
I used it for saving databases of CRM project of clients. With this I am able to access database remotely. And I can manage easily. With this database we can save unstructed data without any issue.