For MongoDB as a service, there are two distinct ways to use it: as a personal user, where one can register on Atlas and experiment with its features; and as a professional, where one can use it for backup management, environment management, and creating figures. Additionally, MongoDB Atlas has features such as data lake capability, the ability to create charts from queries without using other BI tools, and Apache Lucene for text search. I have experimented with these features, but I have not used them professionally. The most relevant use for me is managing backups. Atlas MongoDB also allows for making REST calls and creating applications with triggers, although I have not used it for programming applications much.
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Audio embedding resources
I’d like to suggest adding more resources on using audio embeddings with MongoDB's vector search. Additional guidance on best practices and examples would greatly benefit those looking to work with audio data in MongoDB.
Powerful and Flexible Database for Gen AI Projects, with Room for Onboarding Improvements
Creating Mentation, an AI-driven wellness assistant, was an enriching experience, and MongoDB supplied the foundation we required for effortlessly handling intricate and diverse data. By managing user interactions and emotional data as well as processing vector embeddings, MongoDB effortlessly fulfilled our requirements. Its adaptability and scalability proved essential, allowing us to broaden our project’s scope without having to repeatedly reconfigure the database.
Although the documentation is comprehensive and addresses various use cases, a concentrated, beginner-friendly crash course would have been immensely helpful—particularly for teams such as ours seeking to utilize AWS and Gen AI. Exploring the fundamentals of MongoDB, such as querying, vector indexing, and aggregation pipelines, prompted us to seek out external tutorials, especially to clarify information regarding vector indexing. At one stage, we came across contradictory data from these sources indicating that solely larger M10 clusters were capable of handling vector indexing, which resulted in additional testing and problem-solving.
Although there were some learning challenges, MongoDB demonstrated to be a robust solution for the requirements of our project. By providing a more efficient onboarding process—centered on key elements and better instructions for utilizing features such as vector indexing—MongoDB would become even more attainable for developers engaged with advanced technology. In general, we had a positive experience with MongoDB, and with some modifications, it could easily become the preferred choice for any developer venturing into Gen AI applications.
Improvement on Documentation
For my hackathon project, I chose MongoDB Atlas from AWS Marketplace. I particularly like the auto-scaling capability.
However, I encountered some challenges with the SDKs at multiple stages of use, so I had to look outside the official documentation for help. For example, while connecting to the cluster.
While the existing documentation is okay, it would be more beneficial if video resources were included (as this helps better than textual documentation). Additionally, integrating real-world examples and case studies into the documentation could greatly enhance its practical value.
The best solution out there
I've used mongodb professionally for 4 years and have found the product meets and exceeds the demands placed on it by the products i create.
Easy to deploy, scalable, and has great technical support
What is our primary use case?
How has it helped my organization?
It has a good easy to use gui and the ability to do most of the management operations under automation
What is most valuable?
The most useful feature is the management of the backup. I use a managed tool offered by MongoDB to manage an on-prem environment and compare it with the SaaS service and software. The solution is very ready-to-use and it is much simpler to manage backups, which cuts down on the amount of work and stress. However, at least two other features should be mentioned in the current versions. Search integrated with Lucene and the possibility of storing vector data.
What needs improvement?
There are some Mongo new features that could be useful for the customers I work with, which are related to migration from on-prem to the cloud. MongoDB is currently working on these features. With the latest version of Mongo, there are new tools that help with migrating. However, currently, only Mongo can use these new features. Soon these migration tools should be released to the public and could really assist with migration also from SQL on-prem environment to Atlas.
For how long have I used the solution?
I have been using the solution for four years.
What do I think about the stability of the solution?
The solution is very stable.
What do I think about the scalability of the solution?
I give the scalability a nine out of ten. MongoDB is very easy to scale and with Atlas, it is possible with a few clicks and configurations.
How are customer service and support?
The technical support team is skilled, prepared, and really helpful.
How would you rate customer service and support?
Positive
How was the initial setup?
The initial setup is straightforward. Only one person is required for deployment.
What's my experience with pricing, setup cost, and licensing?
For me, MongoDB Atlas could be expensive as every cloud service because I don't have many other terms of comparison, but I think it is not so expensive for customers. In the end, they may be able to save money rather than buy it on-premise however, on-premise, they do not have access to all the features that Atlas exposes. The costs are similar to having a cloud provider and if we look at the short-term, there is a real saving of money investing in their service instead of making it on-prem in the same scenario.
What other advice do I have?
I give the solution an eight out of ten. I am not familiar with other SQL databases on the cloud. I know that Atlas is quite stable and the service is good, providing customers with all the necessary features to use it as a service. MongoDB Atlas is integrated and available on Google, AWS, and Azure.
I advise people to take advantage of the free courses from MongoDB University that are very well done to gain a general knowledge of MongoDB. Therefore, if someone has no experience with Mongo, they can get great preparation for the MongoDB University course without spending any money.
Which deployment model are you using for this solution?
Public Cloud
You can start quickly on projects which allow you to store many things
Any business types where we need instructional data.
How has it helped my organization?
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.
What is most valuable?
You can start quickly on projects which allow you to store many things.
What needs improvement?
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.
For how long have I used the solution?
One to three years.
What do I think about the stability of the solution?
The stability is very good.
In my previous company, we had a lot of data coming in every day, and the product remained stable.
What do I think about the scalability of the solution?
We have been able to scale from gigabytes to terabytes easily.
How is customer service and technical support?
I have never used technical support.
How was the initial setup?
The integration and configuration of MongoDB in the AWS environment is quite good.
What was our ROI?
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.
Which other solutions did I evaluate?
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.
What other advice do I have?
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.
The integration went well and was lightweight
It is one of the main database back-ends for one of our products in the company.
How has it helped my organization?
* It has a flexible integration with our easy API.
* It has a good, easy integration with other tools that we use for this product.
What is most valuable?
* Flexibility
* An easy API
* Its redundance: We have a cluster of three very solid instances, so its very reliable.
* The integration went well and was lightweight.
What needs improvement?
During the configuration, we did some migrations where we had to reindex about 70,000 indexes, which took around an hour. They should improve this and optimize the indexing.
For how long have I used the solution?
One to three years.
What do I think about the stability of the solution?
We have good impressions of the stability.
We are good as far as the stress that we place on it. This is one part of the product that we are not worried about.
What do I think about the scalability of the solution?
The scalability is good. We use a three instance cluster for this installation, and it works great. Therefore, we haven't had to touch it for awhile, which is good.
How was the initial setup?
Our backups required some configuration.
Which other solutions did I evaluate?
I did not evaluate the product because I am on the operations side and the design was already done.
What other advice do I have?
Look at what MongoDB can do for you in terms of database back-end persistence. I would recommend to look at this first before you start looking at other solutions.
My company is interested in putting out products that are reliable for our customers, which we can monitor easily. We also want them to be easy to install and deploy, which is why I am happy with this one.
We are running this on an AWS instance.
It is nice because our developers create tables whenever they need to sync data
We use it for all of our temporary data, anything which is not warehoused.
It works with AWS Lamda and EC2.
How has it helped my organization?
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.
What is most valuable?
* Autoscaling
* No overhead
* No maintenance
What needs improvement?
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.
For how long have I used the solution?
One to three years.
What do I think about the stability of the solution?
It is very stable. It has been running without issues.
What do I think about the scalability of the solution?
We have about 2000 customers a day.
What's my experience with pricing, setup cost, and licensing?
The pricing is good. We originally chose it over DynamoDB because of the pricing.
Which other solutions did I evaluate?
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.
What other advice do I have?
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.
Its most valuable features are high availability and zero maintenance
* High availability
* Resource recovery
How has it helped my organization?
It brought a lot of confidence to our team.
What is most valuable?
* High availability
* Zero maintenance, to double up things.
What needs improvement?
The cost needs improvement. The product is good, but the cost that we paid for it is expensive, so it wasn't that valuable.
For how long have I used the solution?
Less than one year.
What do I think about the stability of the solution?
The reliability is good.
What do I think about the scalability of the solution?
It is reliable. We have a small environment right now.
How was the initial setup?
The integration and configuration of this product in our AWS environment were easy and straightforward.
AWS works well with this application, but that is the only thing we have tested. We are happy with it.
What's my experience with pricing, setup cost, and licensing?
Purchasing through the AWS Marketplace was easy and seamless. We chose the AWS Marketplace because it is a brand name and a popular product.
It is too expensive. They need to work on this.
Which other solutions did I evaluate?
I also evaluated the open source version of this same product, but chose the AWS version for more reliability and enterprise support.
What other advice do I have?
I would recommend the product.
It was easy and quick to market in terms of getting the application deployed rapidly
It drives a good portion of our client-facing software utilities.
What is most valuable?
* Scalability is its most valuable feature, as it is pretty simple.
* The maintenance is fairly easy.
* It was easy and quick to market in terms of getting the application deployed rapidly.
What needs improvement?
The cost needs improvement.
For how long have I used the solution?
Three to five years.
What do I think about the stability of the solution?
The stability is fine.
How is customer service and technical support?
We use technical support quite frequently. The tech support experiences that I have heard anecdotally have been fine. I haven't heard about any issues of getting problems resolved.
We are mostly using technical support because of changes in deployments and learning how to configure new things. While a lot of the work is done in-house, it is more about extending the capabilities of our internal team.
What's my experience with pricing, setup cost, and licensing?
Pricing could always be better.
Which other solutions did I evaluate?
I am sure that they evaluated other products, but it's been in deployment since I have been with the company. Therefore, I don't know if they looked at other types of databases at that time.
What other advice do I have?
It is a great product. It works fine, so we recommend it. We are continuing to use and expand it.
Right now, MongoDB is deployed for a very specific use case. However, it is something that we always consider when we are looking to migrate away from traditional RDBMS, like Oracle and SQL Server, then MongoDB is on the top of that list. We see if it is capable of supporting the app as written.
I was not involved in the implementation or configuration.
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