MongoDB Atlas (pay-as-you-go)

What do you like best about the product?

The flexibility of its schema, and the amount of scalability it provides, be it horizontal or vertical. Aggregation & high availability makes it a wonderful choice. Extremely easy to use and integrate with any language, make it the first choice.

What do you dislike about the product?

Duplicity and no native joins are a concern.

What problems is the product solving and how is that benefiting you?

I had integrated ML features in my application, and SQL based databases, were a nightmare, so I switched over. Now, most of my applications are using mongo.

What do you like best about the product?

Flexible schema, scalability and high performance ,built in horizontal scaling with sharding (distributes data across multiple servers).

What do you dislike about the product?

When it comes to data consistency compared to SQL, this system by default emphasizes availability and partition tolerance, as described by the CAP theorem. Achieving strong consistency is possible, but it demands careful setup, particularly in configuring write concerns and read preferences.

What problems is the product solving and how is that benefiting you?

Rigid schemas are a hallmark of traditional SQL databases, which require you to define a fixed structure in advance. When your application changes rapidly—such as when you introduce new features or fields—updating the schema can be a cumbersome process. In contrast, MongoDB addresses this issue with its flexible schema approach, allowing you to add or modify fields in your documents without causing downtime.

What do you like best about the product?

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.

What do you dislike about the product?

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.

What problems is the product solving and how is that benefiting you?

So the main problem MongoDB solves for us is handling all this unstructured and semi-structured data. Like in our insurance systems, all these different partners send over data that's slightly different, with fields that are always changing or totally optional. With SQL it was a huge pain to constantly be altering tables, but with Mongo we just take the JSON and store it as-is, which honestly saves us a ton of time. We can just prototype and push feature super quick without getting stuck on some rigid schema designs. It makes the team way more agile and we don't have to rely on a DBA for every little schema change. Scalability is another area where it really helps. Once the dataset gets huge, we can scale out with replica sets or sharding without a massive rewrite on the code side. For stuff that's really read-heavy, it performs great—once you finally get the indexes sorted out anyway . Overall, it just lets us move faster, handle messy, evolving data, and there's a lot less friction between us backend devs and the whole database structure thing.

What do you like best about the product?

Below are the features which i like the most about the db:
1. scalability and performance
2. robust managed service
3. flexible data model

What do you dislike about the product?

The only things that concern me are the cost of the D,B which can spike with the scale

What problems is the product solving and how is that benefiting you?

Below are the major problems which is being solved by the mongodb
1.flexible data handling
2.high avaialability and scaling
3.Manged operation with atlas like auto backup , monitoring etc

What do you like best about the product?

MongoDB’s document-oriented architecture uses JSON-like BSON documents for flexible, schema-less data storage. This allows dynamic adaptation to evolving data structures without rigid schema migrations.

Horizontal scalability via sharding efficiently distributes data across clusters, enabling seamless handling of massive datasets.

The aggregation framework supports complex data transformations, while built-in geospatial indexing and full-text search expand analytical capabilities.

Transaction support (from v4.0) ensures ACID compliance for multi-document operations.

What do you dislike about the product?

The transition from SQL can involve a steep learning curve, particularly for complex queries and aggregation pipelines.

Storage consumption is higher than relational databases due to denormalized data structures, impacting cost efficiency at scale.

While transactions are supported, performance tuning for complex ACID operations requires meticulous indexing and schema design.

What problems is the product solving and how is that benefiting you?

MongoDB eliminated rigid schema constraints, allowing our team to rapidly prototype and iterate applications with unstructured data. It streamlined handling high-velocity data streams in IoT projects, avoiding costly schema redesigns during development cycles. The scalability features supported our transition from prototype to production without operational bottlenecks, directly accelerating time-to-market for new features