MongoDB Reviews & Product Details

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.

Flexible schema, scalability and high performance ,built in horizontal scaling with sharding (distributes data across multiple servers). Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

Duplicity and no native joins are a concern. Review collected by and hosted on G2.com.

MongoDB excels with its flexible document model, which allows for dynamic schema design—making it perfect for fast-paced development cycles and agile teams. Its JSON-like BSON storage format aligns well with modern JavaScript-based stacks like MERN, ensuring smooth data handling from front end to backend. The built-in horizontal scaling, support for geospatial queries, and full-text search are game-changers in terms of versatility. Review collected by and hosted on G2.com.

While MongoDB is powerful, it does have some drawbacks. It can consume significantly more storage than traditional relational databases due to its denormalized document structure. For applications with complex relationships, performance tuning requires careful indexing and schema design. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

Below are the features which i like the most about the db:

1. scalability and performance

2. robust managed service

3. flexible data model Review collected by and hosted on G2.com.

The only things that concern me are the cost of the D,B which can spike with the scale Review collected by and hosted on G2.com.

MongoDB's flexibility and scalability are standout features. Its document-oriented model (using BSON) allows for dynamic, schema-less data structures, making it super versatile for evolving applications. This is especially helpful when dealing with unstructured or semi-structured data.

I also appreciate its horizontal scaling capabilities through sharding, which makes it suitable for handling large datasets and high-throughput applications. Features like indexing, aggregation pipelines, and replica sets for high availability are excellent for both performance and reliability.

For developers, tools like MongoDB Atlas (its cloud platform) simplify deployment and monitoring, saving tons of time. Review collected by and hosted on G2.com.

write amplification and potential performance issues under high write loads if not tuned properly. Its flexibility can also be a double-edged sword; having no enforced schema can lead to messy data structures if developers aren't disciplined. Review collected by and hosted on G2.com.

My favorite feature in this database is the flexibility of its use as well as the possibility to scale it. Because this model stores data in JSON-like formats, it is possible to handle unstructured and semi-structured data without having to prescribe very specific data models. This flexibility is especially good for application where the structure of the data being stored can change as time passes. Being able to scale a database horizontally through the use of sharding is one of MongoDB’s best features since it helps in loading big data and is efficient when dealing with traffic loads. Also, its complex query language; the power offered by the aggregation framework and indexing and data retrieval make the process very efficient and diverse. Moreover, features such as the MongoDB Atlas make cloud deployment and management easy and more enjoyable. MongoDB has gained many supporters of the community and had a great documentation, which makes it fit for today’s developments. Review collected by and hosted on G2.com.

Probably one of the biggest negatives of the MongoDB is its steep learning curve for those that have no prior experience with NoSQL systems or have recently migrated from SQL. On the positive side, it is also very flexible, allowing developers to easily create badly thought out schemas, which when the application starts getting a lot of use can slow down the performance immensely. Also, handling shard and replication in self-serving environment quite challenging and may need good understanding of structure. A third anotated limitation is the ACID properties of transactions while MongoDB has added support for these recently and to a far lesser extent than traditional relational database systems, it may not be suitable where high consistency is critical. Finally and as for the offering of MongoDB Atlas, which is a cloud managed service of MongoDB, there is a high likelihood of accumulating high costs particularly for those that are intending to develop jumbo scale applications for their start-ups or small business enterprises. Review collected by and hosted on G2.com.

Our application development and data analysis initiatives have relied heavily on MongoDB, a highly scalable and versatile NoSQL database, for its ability to efficiently manage unstructured and semi-structured data. The database provides a feature called indexing, which assigns a unique ID to each row. I've found this to be very helpful in today's world, where web services process massive amounts of data and better storage and resource utilization is essential; in addition, its aggregation capabilities allow me to perform complicated, resource-intensive queries at lightning speed. Review collected by and hosted on G2.com.

Starting and writing aggregations in MongoDB can be challenging without a good tool to guide you. You'll also need a basic understanding of databases and SQL queries to understand the concepts. Review collected by and hosted on G2.com.

Fast data fetching and easy to use and implementaion. Review collected by and hosted on G2.com.

Some time we face connective issue with the database. Without any appropriate reason Review collected by and hosted on G2.com.