I like the basic architecture of MongoDB and how easy it is to find my JSON with Python libraries. It provides a good score with Python libraries, making data export, encryption, and decryption very easy. The latest feature about vector databases is just amazing for me as an AI engineer and has changed the landscape for me. I no longer need to use any other vector database, and I'm really comfortable using MongoDB. The initial setup was very easy, especially with the Mongo Compass and the resources provided for Python, which make it easier than any other setup. Review collected by and hosted on G2.com.

The major thing with the record databases is that you need to set them up manually most of the time. I would prefer if there's a setup to define everything from Python code rather than having to go into the Mongo interface and change it there. They don't provide automatic integration of vectorized databases from the Python code, which is a bit of a setback for me. Review collected by and hosted on G2.com.

MongoDB Atlas is a fully managed cloud database service for MongoDB Review collected by and hosted on G2.com.

Major dislike is it is very costly than on prem MongoDB, very less control over servers and OS as it is saas model Review collected by and hosted on G2.com.

I use MongoDB Atlas for a document database and appreciate its faster response and easy search with indexing. I really like sharding in MongoDB Atlas because it splits the data equally to all the nodes, which allows it to handle multiple reads and write operations. Setting up MongoDB Atlas is straightforward and easy. Review collected by and hosted on G2.com.

I am not a fan of the default ID that MongoDB Atlas creates for every entry. Review collected by and hosted on G2.com.

MongoDB is a highly flexible database system that brings several benefits, including support for document nesting and partial indexing across various fields. It continues to allow for robust aggregations, enabling the use of filters and regex operations. At the same time, MongoDB offers a more developer-friendly approach to viewing and modifying any JSON-type documents.

We have choose MongoDB for its inherit flexible and because it scales very well, which is exactly what we need. Review collected by and hosted on G2.com.

At times, it can be difficult to determine exactly how much data is being retrieved during an aggregation. Having this information readily available while performing such actions—whether in MongoDB Compass or similar tools—would be a significant advantage for assessing performance concerns and overall efficiency. Review collected by and hosted on G2.com.

MongoDB's best part is the flexibility it gives you as a developer. That schema-less structure makes it super easy to just start building something without overthinking all your tables and relations like you do in SQL. On my last project, we had to handle this dynamic insurance data where the fields weren't fixed at all, and Mongo just handled it perfectly. It's really easy to use, especially if you're already comfortable with JSON, 'cause the documents just feel natural. Integrating it with Spring Boot was smooth too – I didn't have to spend a ton of time configuring things, you basically just plug in the driver and go. Implementation-wise, it's not super heavy compared to some other databases, and scaling with replica sets and sharding works decent once you get the hang of it. For customer support, I've never used the enterprise version, but the community forums and the docs are pretty strong; I usually find answers quick. I use MongoDB a lot for side projects and at work, especially when the speed of development matters more than having a super strict schema.Overall, it just feels modern and fast and developer-friendly. It might not be the perfect choice for every single thing, but for projects where the requirements are always changing, MongoDB really saves you time. Review collected by and hosted on G2.com.

Yeah, what I don't love about MongoDB is how the performance can just fall off if you don't stay on top of your indexes. At first everything's super fast, but once your data gets bigger, some queries just start dragging and you realize you gotta spend all this time tuning indexes.And they do have transactions now, which is good, but it's still not as strong or smooth as what you get with a relational DB like Postgres. For stuff where you need really strict consistency, Mongo can feel a little risky sometimes. I also think the aggregation framework has a pretty high learning curve. Some queries that would just be a simple JOIN in SQL end up being these crazy long pipelines in Mongo, and it can get messy. It's a solid tool for sure, but it's definitely not a "set it and leave" kind of deal. You really gotta keep an eye on it and tune things regularly. Review collected by and hosted on G2.com.

I appreciate MongoDB Atlas for making database management more user-friendly with its intuitive UI, which makes it more comfortable to work with compared to using only the terminal. The feature for managing MongoDB aggregations is particularly beneficial, allowing me to build queries from smaller parts efficiently and intuitively, making the process significantly easier than doing it manually. I highly value how MongoDB Atlas helps me work seamlessly with databases, especially when I am developing and need to check the state of my data. Its performance is fast, which I like, and it integrates well when I am working on the backend with Visual Studio Code. Overall, it's easy to set up if environment variables are configured correctly, making the whole process straightforward. Review collected by and hosted on G2.com.

I think it works great , I don't see anything to improve particularly Review collected by and hosted on G2.com.

Reachable and always ready. Its easy to use. I dont need to make my own onpremise clusters anymore, i can use that time more productively with Atlas ! Review collected by and hosted on G2.com.

Everything is ok. Free tier is little slow but okay fair enough. Review collected by and hosted on G2.com.

Basically being as a developer i used it for making my schemas for backend in database and it have advantages of bson type structure which helps me to store the values of realtime type data and it helps me to implement aggregation pipeline as well as use the free tier of database of 512 mb which can be used in mongodb compass Review collected by and hosted on G2.com.

Nothing everything is fine just vpc connection is quite harder for new person Review collected by and hosted on G2.com.

MongoDB supports horizontal scaling so it works well for large applications and growing data. Review collected by and hosted on G2.com.

very high memory uses, MongoDB performs best when indexes fit in RAM. Review collected by and hosted on G2.com.

Automated scaling, backups, monitoring and performance alerts make it incredibly easy to maintain clusters without dedicating a team to infrastructure. Added to that, the UI is intuitive, queries run fast and features like Atlas Search, Charts and built-in security controls help ship features quickly. Review collected by and hosted on G2.com.

Some configuration options feel hidden behind tiers. Also, greater transparency around cost optimization or in-platform recommendations would make the experience even smoother. Review collected by and hosted on G2.com.