We restore our golden data from various sources and then push it to MongoDB. We make our CDP from MongoDB, which serves as a device-centric system.
MongoDB Atlas (pay-as-you-go)
MongoDB, IncExternal reviews
515 reviews
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External reviews are not included in the AWS star rating for the product.
MongoDB Made Easy: Simplifying Data Management for Everyone
What do you like best about the product?
MongoDB makes it simple to work with data, like storing and finding data quickly.
It can handle large volume of data without slowing down.
It is easy to use even if you are not expert.
It is very secure so the only right people can access the data.
It is easy to integrate in code.
The schemaless architecture makes it very useful for raw and especially json data.
It can handle large volume of data without slowing down.
It is easy to use even if you are not expert.
It is very secure so the only right people can access the data.
It is easy to integrate in code.
The schemaless architecture makes it very useful for raw and especially json data.
What do you dislike about the product?
Using mongoDB might cost high especially for bigger projects with lost of features.
Sometimes it might have bugs or issues that need fixing.
Sometimes it might have bugs or issues that need fixing.
What problems is the product solving and how is that benefiting you?
MongoDB is ideal for storing and retrieving unstructured data efficiently, supporting diverse data types and formats.
It's well-suited for handling large volumes of unstructured data, ensuring smooth performance and scalability.
It's well-suited for handling large volumes of unstructured data, ensuring smooth performance and scalability.
Quick DB
What do you like best about the product?
Ability to handle growing data volume, evolving data models.
What do you dislike about the product?
Learning ios required to make full use of the product.
What problems is the product solving and how is that benefiting you?
Ingest volumes from any data model.
A stable solution with Autoscaling feature with easy setup
What is our primary use case?
What is most valuable?
There is a built-in feature called Autoscaling In MongoDB Atlas. This feature automatically adjusts the configuration of MongoDB based on the volume of users we ingest daily. Autoscaling dynamically scales the resources to accommodate the load when our data flow increases.
What needs improvement?
The real-time data visible within MongoDB Atlas is not accurate. If they can improve the UI that monitors real-time data. It's more impressive and more attractive. It could be more user-friendly.
For how long have I used the solution?
I have been using MongoDB Atlas for two years.
What do I think about the stability of the solution?
The product is pretty stable.
What do I think about the scalability of the solution?
The solution is scalable. Autoscaling supports it.
50 users are using this solution
How are customer service and support?
Whenever we have doubts during configuration, we reach out for assistance. We must upgrade certain parameters in our MongoDB setup, prompting us to contact their support team. They resolve such issues within four to five hours.
How was the initial setup?
The initial setup is not very complex. It is easy to use. It's easy to deploy on MongoDB. We push from GitHub. From there, we specify where the data is restored in MongoDB. We continue to connect. It puts the data and delivers it to Argo City.
What's my experience with pricing, setup cost, and licensing?
The product has a yearly subscription.
What other advice do I have?
We have assigned DevOps for security.
The overview and monitoring part will address this issue, and then we will use it to observe any increasing traffic on our website. We also monitor the rising number of connections due to this traffic. It's quite easy to oversee everything in one place. However, the UI isn't particularly user-friendly.
I've also used it in my previous company and found it handy and easy to configure, including easy capabilities.
We are establishing SLAs that are directly tied to MongoDB. All are interconnected with MongoDB. If MongoDB experiences downtime or RAM or CPU usage spikes significantly, users may encounter difficulties logging in. This reliance on MongoDB can pose challenges for user accessibility, particularly when considering the conferencing tools we use.
Overall, I rate the solution an eight out of ten.
Truly scalable database for Read heavy and write system.
What do you like best about the product?
The low latency and scalability of database with increasing work load. We migrated one of our system from firestore to mongoDB and loving the performance which we are getting.
What do you dislike about the product?
sometime feels like perfect database for true scale but we need to carefully manage index and add proper index to make query efficient.
What problems is the product solving and how is that benefiting you?
I our use case we use to store every datapoint for user details like location and ip in firestore. We are suffering from costing and latency problem as we are growing. We now shifted to mango db initial their is high resource usage by mongoDB but as we tune configurations and added indexing we no moving having resource usage problem.
Offers performance, maintenance, and simplifies things by automating previously manual tasks
What is our primary use case?
We use it in a cloud setup on Google Cloud Platform as part of a microservices-based cloud solution. These microservices communicate with messages, and one use case for MongoDB is storing specific messages we're interested in.
How has it helped my organization?
MongoDB has supported our organization's need for scalable and flexible data storage.
We use it internally, where different teams manage different microservices. Sometimes, internal incidents arise, requiring teams to dedicate personnel to resolve and communicate with other teams.
With MongoDB, other teams can now access some of our data and investigate issues on their own, freeing up personnel for other tasks.
Moreover, this solution simplifies real-time data analytics or application development for our business.
It simplifies things by automating previously manual tasks. It acts as a self-service portal for our team, reducing manual work and enabling automation.
What is most valuable?
We're happy with the performance, maintenance, and especially the ease of use within Google Cloud.
Given our microservices architecture, it's like a large puzzle, and MongoDB feels like it fills the gaps we were facing. So, the global clusters feature has enhanced our application performance and user experience.
It helps us optimize team performance, which is valuable.
What needs improvement?
The initial configuration could be a bit easier.
For how long have I used the solution?
I have been using this solution for a couple of years.
What do I think about the stability of the solution?
We've experienced some issues, but most MongoDB issues are resolved quickly. The issues we face are mainly with other systems.
So, it is a stable solution.
What do I think about the scalability of the solution?
It is a scalable solution because we use quite a lot of data, and it handles it well.
It's a microservice solution, so each microservice runs on several pods, maybe eight. Each pod uses MongoDB and makes its own connections, so multiply by eight, maybe 100, so roughly a thousand users.
These are internal users, so we're fine with the current number.
How are customer service and support?
MongoDB offers free support online, and they seem to be doing a good job overall.
Which solution did I use previously and why did I switch?
We have used other databases as well, including Google Cloud, for the past two years on our current project. My company policy guides such decisions. Overall, the company is happy with MongoDB.
How was the initial setup?
The setup is automated through our partner using Terraform for provisioning, not just for MongoDB but for our whole infrastructure. We manage daily deployments using TerraForm, and MongoDB setup on Google Cloud is very smooth.
The deployment is very quick. For example, microservices using MongoDB start very quickly, possibly within a minute.
We haven't had major issues with deployment or configuration. Maybe initial configuration fine-tuning for performance can be time-consuming, but the initial effort pays off later with reduced maintenance needs.
Expertise in automation and deployment processes is helpful and worth learning within the team.
What about the implementation team?
We do it in-house. It's integrated with Google Cloud, GitHub, and GitLab actions. Everything is cloud-based and easy to work with. It's been continually improving over the years.
We don't use external consultants, as we have in-house expertise. It's a 100% cloud solution.
We don't have engineers dedicated to maintenance. It's part of our continuous integration and delivery environment, so there's not much manual intervention needed. Issues usually arise when deploying incorrectly and rolling back, but deployment itself is straightforward.
What was our ROI?
In some teams, companies, and projects, there might be two to three people dedicated to everything, which is a lot. If these skills to analyze productivity or cost saving can be automated, these people can teach others and do more valuable work. It's all win-win.
What's my experience with pricing, setup cost, and licensing?
The price is cheap enough. It is comparable and has average pricing. We have a long-term license.
The pricing is acceptable for enterprise tier.
What other advice do I have?
We haven't faced any major issues so I would rate this solution a nine out of ten.
In this project, it's more integrated than previous ones. The level of integration, automation, and evolution is impressive when used well. It's flawless, straightforward, and hassle-free.
Easy to scale and offers good performance and stability
What is our primary use case?
It's good for performance and stability if you need a non-SQL database to store data.
How has it helped my organization?
We use it as a database for some of our microservices. We use it as a database for a few of our microservices.
What is most valuable?
The stability and performance are great. The high availability feature is great.
Moreover, I am happy with the automated backup and restore functionality.
What needs improvement?
In the past, MongoDB offered more features for free, but now it's quite limited. The free version is limited, and you need to pay extra to fully utilize it.
The pricing could be improved.
For how long have I used the solution?
I have experience with this solution. I've been with this product for a couple of years.
What do I think about the stability of the solution?
It is a stable solution. I would rate the stability a nine out of ten.
What do I think about the scalability of the solution?
It is a scalable product, but only if you use the paid features. And if you enable sharded cluster functionality, it scales very well.
How was the initial setup?
The initial setup is very straightforward.
The ease of setting up and maintaining your database clusters with MongoDB depends on the features you need. If you only need basic functionality, setup can be simple. But for additional features like reliability and backups, it might require a more complex configuration.
What about the implementation team?
We did it in-house.
What other advice do I have?
Overall, I would rate the solution a nine out of ten. I would recommend using this product.
If you need a no-SQL database, then MongoDB is a good choice.
Very Good Non-Relational Database
What do you like best about the product?
I mostly liked the easiness of using MongoDB. We don't have to define table structure. We can add a new column in our data time as it is completely based on JSON.
What do you dislike about the product?
I don't have anything to dislike about MongoDB.
What problems is the product solving and how is that benefiting you?
I used MongoDB in a couple of my Java projects. I used it to store user login activity and logs.
Perfect NoSql database for High available Microservieces
What do you like best about the product?
NoSQL yet supports schema
Support for geospatial indexing with sharding, replication
Pipeline aggregation
Vast community support and client library in every language
Readymade connector with changelog to elastic search , kafka etc
Support for geospatial indexing with sharding, replication
Pipeline aggregation
Vast community support and client library in every language
Readymade connector with changelog to elastic search , kafka etc
What do you dislike about the product?
Lack of analytical stack
Complex sharding operation with manual balancing
Complex sharding operation with manual balancing
What problems is the product solving and how is that benefiting you?
Storing evolving schema database for our SaaS microservices.
A convenient database that is simple to use
What is most valuable?
The product is simple to use and enterprise-ready. It is also open-source.
What do I think about the stability of the solution?
I rate the product's stability a nine out of ten.
How was the initial setup?
The tool's deployment is easy. We used Amazon EC2 Containers to deploy it.
What other advice do I have?
MongoDB Atlas is a convenient database that you need to start using. I rate it a nine out of ten.
A performant NOSQL database
What do you like best about the product?
Flexible document base data models, easy to use and implement with various languages, large community for questions and tutorials, its query language and reliable in production applications
What do you dislike about the product?
has a learning curve if coming from sql based databases, things like joins, data integrity and schema validation are not available here. usually you know these drawbacks when you choose nosql
What problems is the product solving and how is that benefiting you?
Our main db is in mongo. We have our API service store and fetch our data from this. We have other services query on it for analytics and machine learning.
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