Open-source tool improves network monitoring and reporting efficiency
What is our primary use case?
MongoDB does well in being able to access our network devices and keep logs and reporting—that's about it.
I would recommend MongoDB as part of a template if anyone is considering free and open-source templating services such as LibreNMS, but as a standalone, I couldn't advise.
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.
Which deployment model are you using for this solution?
On-premises
Offers reliable engine for legacy needs but requires enhanced cost management and AI features
What is our primary use case?
I am not a partner of MongoDB; I am just a customer.
I do not use MongoDB in AI projects; only CosmoDB is used for AI projects, as MongoDB is an old pattern for us, and the new workload in AI is for a new pattern, which is CosmoDB for AI apps.
I would recommend MongoDB because it is a good pattern and a good product for legacy; for us, MongoDB is for legacy databases and legacy apps, and in this scope, it is a good pattern and a stable database engine; however, for new deployments and new applications, CosmoDB is a better engine.
What is most valuable?
My experience as a partner with Microsoft is very good because we have been a partner for three or four years, and it has been a very good experience.
MongoDB may have advantages over Cosmos DB perhaps in metrics because you can make some dashboards with database metrics, and there are many tools in MongoDB for dashboarding that are perhaps better than CosmoDB.
The dashboards in MongoDB have more functionalities; for example, you can create a dashboard with MongoDB database data, and it is simple to create, such as some sales dashboards, while I do not see this functionality to rapidly create such dashboards in CosmoDB.
What needs improvement?
While MongoDB is a good product, it is also an expensive product for support, and its scalability is acceptable, but the big problem with MongoDB is the cost.
For security in MongoDB, we work with encrypted databases by default, but we have not contracted the security options in our contract because it is too expensive, so we only implement encrypted databases without the security pack, which is very expensive for us; in security, we are at the first steps, just using encrypted databases.
I think additional features needed in MongoDB include perhaps vector databases, as I think they are not supported right now.
For how long have I used the solution?
I have been working with MongoDB for five years.
What do I think about the scalability of the solution?
The scalability in MongoDB is limited because we only work with ReplicaSet with two servers, and in comparison, the scalability in CosmoDB is much better than the MongoDB ReplicaSet models; although you can set the auto-provisioning of a node in ReplicaSet, it is very expensive, and we have to work with manual scalability in MongoDB.
The performance of MongoDB is good, especially in a ReplicaSet model, but if you want to pass on to another model, for example, Sharding models, it is very complicated; in ReplicaSet, it is acceptable, but if your workload needs more performance, and you must pass to a Sharding model, it is complicated in MongoDB, whereas in CosmoDB, it is simple.
What was our ROI?
We have seen a little ROI, and we want to target CosmoDB for this return on investment because it is the better model for this feature; however, with MongoDB, it is difficult to calculate the return on investment, as it is too expensive for our use.
What's my experience with pricing, setup cost, and licensing?
We pay approximately 2,000 euros per month for MongoDB.
What other advice do I have?
This solution receives a rating of 7 out of 10.
Friendly to use of collections
What do you like best about the product?
The mongodb GUI is very good to view the collection and manage to the databases
What do you dislike about the product?
The GUI of we cannot see the user details
What problems is the product solving and how is that benefiting you?
Easy to edit collections
Transforms data flow with adaptable schema and smooth public cloud deployment
What is our primary use case?
One of our business units uses
MongoDB, and we developed an ETL pipeline that extracts data from
MongoDB and transfers it into our data warehouse.
What is most valuable?
MongoDB is a NoSQL database that is similar to a document database. It offers flexibility in schema adaptation, allowing us to change the schema and add new data points. Additionally, it scales up easily with low memory requirements. This makes it suitable for our data management needs.
What needs improvement?
There is room for improvement in integrating MongoDB with agentive AI solutions. While solutions for other databases like SQL or
PostgreSQL already exist, MongoDB requires additional integrations for developing AI solutions.
For how long have I used the solution?
I have about four years of experience working with MongoDB.
What was my experience with deployment of the solution?
The deployment process was straightforward.
What do I think about the stability of the solution?
MongoDB is highly stable, and I would rate its stability at nine out of ten.
What do I think about the scalability of the solution?
MongoDB is highly scalable. I would rate its scalability nine out of ten.
How are customer service and support?
We use the open-source version of MongoDB and manage it ourselves, so we have not contacted their technical support.
How would you rate customer service and support?
Which solution did I use previously and why did I switch?
Before using MongoDB, we used IBM
DB2. We switched to MongoDB to develop a composite system that includes both SQL and NoSQL databases.
How was the initial setup?
The initial setup of MongoDB was a straightforward process.
What's my experience with pricing, setup cost, and licensing?
We use the free version of MongoDB, so there are no licensing costs.
What other advice do I have?
Based on my experience, I would recommend MongoDB to others. Its usage depends on specific use cases. MongoDB is suitable for document database needs. I would rate MongoDB as eight or nine out of ten, and I would rate the overall solution the same.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Other
Overpriced, Poor performance and some of the worse support I have ever had to deal with
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.
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.
Leverages public cloud and ease to use but support response time requires improvement
What is our primary use case?
We used MongoDB on AWS for a specific project.
What is most valuable?
We put MongoDB on AWS for a specific project. It's easy to use.
What needs improvement?
If something is wrong on the cluster, then you need to contact the support team. The stability could be better.
For how long have I used the solution?
I used MongoDB for about a year.
What do I think about the stability of the solution?
It's okay. It's acceptable. The stability could be better.
How are customer service and support?
If something is wrong on the cluster, you need to contact the support team. At first, when we were trying to build a cluster.
How would you rate customer service and support?
What other advice do I have?
We rated MongoDB a seven out of ten.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
Efficiently manage data with adaptable and user-friendly query functions
What is our primary use case?
I use MongoDB to connect our backend with the MongoDB database. Once connected, it allows us to store and manage our data efficiently.
It's particularly useful because MongoDB is a document-oriented database, so it doesn't require predefined schema definitions which MySQL does. I've used MongoDB in two to three projects.
What is most valuable?
The most valuable feature of MongoDB is the predefined functions available when using Node.js. These functions simplify the query process, making it user-friendly and straightforward.
Additionally, MongoDB's flexibility in not requiring a predefined schema makes it adaptable to changes.
Another advantage is the straightforward deployment process, especially when deploying on our own server.
What needs improvement?
I haven't used MongoDB extensively, so I can't pinpoint a specific area that requires significant improvement at this time.
For how long have I used the solution?
I've used MongoDB in two to three projects.
What do I think about the stability of the solution?
I haven't faced any breakdowns or stability issues with MongoDB.
What do I think about the scalability of the solution?
MongoDB is easy to scale up or down, making it flexible for varying data needs.
Which solution did I use previously and why did I switch?
I did certification in AWS in 2023 and used AWS during that period and had about a month of experience using it for basic deployments. However, there hasn't been any work since.
How was the initial setup?
At the start, connecting to the database via Compass or through a direct ID was a challenge. However, once the procedure is clarified, it becomes straightforward.
What other advice do I have?
I would recommend MongoDB because it is widely used by many organizations. It is beneficial to learn MongoDB as it is a common requirement in various projects and companies.
I would rate MongoDB nine out of ten.
Which deployment model are you using for this solution?
On-premises
Flexible schema and replication with enhanced document handling
What is our primary use case?
We use MongoDB for handling document-based databases, specifically for sending unemployment forms using Form IO.
In remote areas where technology is not widely available, the forms can be scanned and uploaded, and they are stored as key-value pairs in the MongoDB NoSQL database.
How has it helped my organization?
MongoDB allows us to store unstructured data with flexibility. It has enhanced our ability to file unemployment processes for individuals who cannot access the system to create a claimant ID.
What is most valuable?
The most valuable features of MongoDB include the flexible schema for storing data, its replication capabilities with high availability through a replica set setup, and horizontal scalability using sharding.
What needs improvement?
There was a need for integrating relational database capabilities, however, MongoDB has introduced a relational converter that allows conversion between SQL and NoSQL.
For how long have I used the solution?
We migrated to MongoDB back in 2019 during the COVID period.
What do I think about the scalability of the solution?
MongoDB scales horizontally using sharding, which is efficient and enhances performance by reducing load and increasing speed.
Which solution did I use previously and why did I switch?
We used a traditional SQL database before moving to MongoDB. My exposure to MongoDB's ability to handle unstructured data was compelling.
How was the initial setup?
The initial setup was easy, largely due to my preparation for certification and the support from site reliability engineers and architects.
What about the implementation team?
The implementation was assisted by a site reliability engineer, and I prepared a playbook for guidance.
What's my experience with pricing, setup cost, and licensing?
I am not entirely aware of the exact pricing details, however, MongoDB is a fairly valued product.
What other advice do I have?
MongoDB is an excellent choice for those seeking flexibility in storing unstructured data. Its replication, high availability, and horizontal scaling through sharding make it very valuable. Understanding JSON and gaining certification can greatly aid in leveraging MongoDB effectively.
I'd rate the solution ten out of ten.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Other
Enhancing data management flexibility with document-oriented style and geospatial capabilities
What is our primary use case?
Our primary use case is mainly for web applications.
What is most valuable?
The document-based style is valuable as it allows for easy addition of sub-documents, unlike a relational database. It adds flexibility and facilitates data management. The geospatial index feature is also useful for dealing with latitude and longitude data.
What needs improvement?
The free tools, like MongoDB Compass, could be enhanced. This is especially relevant for the IDEs or similar tools.
For how long have I used the solution?
I have been using MongoDB for about ten years or so. I am not certain of the exact years, however, it has been since almost version three.
What do I think about the stability of the solution?
MongoDB is quite stable. I haven't encountered any application-breaking problems with it. It handles backups well and doesn't have significant disadvantages.
What do I think about the scalability of the solution?
I rate the scalability of MongoDB as eight out of ten. It is used for very large databases and is very useful, although we don't use it much.
How are customer service and support?
MongoDB has tech support and customer support, however, I have not personally contacted them.
How would you rate customer service and support?
Which solution did I use previously and why did I switch?
I have evaluated RDBMS, MySQL, and Azure SQL previously. MongoDB's advantage is its flexibility as a document database, though it doesn't mean it's better than other databases. It depends on the implementation.
How was the initial setup?
The initial setup is relatively easy, similar to setting up MySQL or other databases.
What was our ROI?
I am not sure about the return on investment as I don't have knowledge regarding the purchase and related aspects.
What's my experience with pricing, setup cost, and licensing?
MongoDB is free of charge. that said, there is also a paid version. We use both free and paid versions.
Which other solutions did I evaluate?
I evaluated RDBMS, MySQL, and Azure SQL.
What other advice do I have?
To start with MongoDB, I recommend reading their documentation, as it is quite sufficient.
I'd rate the solution nine out of ten.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Other
Provides free packages for freshers
What is our primary use case?
I am basically a developer and also a freelancer. I take up a lot of freelance projects for which I use MongoDB. I use it for the database system on my website.
What is most valuable?
The tool provides some free packages for freshers, which is very good because a lot of beginners or students don't want to spend too much money on it. The tool is also user-friendly. I don't make any connections a lot of the time if I use MongoDB in my project.
What needs improvement?
I previously encountered some issues with the tool, which included downtime issues. Sometimes, the tool goes down temporarily. There are some stability issues in the product.
There are some problems with the tool's website, and it can get laggy, but otherwise, it is pretty good.
For how long have I used the solution?
I have been using MongoDB for more than a year. I am just a user of the tool.
What do I think about the stability of the solution?
The tool works most of the time, but it may go down at times. Stability-wise, I rate the solution a seven out of ten.
What do I think about the scalability of the solution?
The tool's scalability is pretty good. Scalability-wise, I rate the solution an eight out of ten.
How are customer service and support?
MongoDB is pretty popular, and we have a lot of documents and support available for it. The community is pretty big for it. I never faced any problems.
Which solution did I use previously and why did I switch?
I have a little experience with SQL, but. I have major experience with MongoDB because it is well compared to other tools.
How was the initial setup?
The product's initial setup phase is easy.
The product's deployment phase can be done quickly. In a few minutes, we can create a database, get the APIs, and use it without any issues.
What's my experience with pricing, setup cost, and licensing?
The pricing is normal. Price-wise, the product is not too much expensive.
What other advice do I have?
Though the replication features in the product are pretty good, I don't use them a lot.
I definitely recommend the tool to other people. A lot of startups can use it, and some people can already use it. If some students want to do some project, they can use the tool as its pricing is reasonable. The support and stability of the tool are also okay.
I rate the tool an eight out of ten.