9 Advantages of MongoDB: Why Modern Teams Choose the World’s Leading NoSQL Database

Many teams turn to MongoDB when applications are required to process rapidly changing data, massive scale, and rapidly changing development cycles. It’s the most popular NoSQL database, and it’s vastly different from a traditional relational database — and it’s something that is really beneficial in the right use cases.

MongoDB is a NoSQL database that stores data in documents or flexible JSON-like structures. The key benefits are that it implements a schema flexible data model, scales horizontally with sharding, is highly available with replica sets, has excellent performance in large scale and accelerates app development for new teams.

Let’s look at the 9 benefits that make MongoDB a “must use” database.

1. The Flexible Schema-less Model for Documents

Data is stored as documents in BSON (binary JSON) format, which means that each record can have a different structure. Fields can be added without migrating an entire table, which is great for changing requirements and data that doesn’t always fit into rows and columns.

2. This Is Horizontal Scalability via Sharding

This is horizontal scalability using sharding.

Scalability is achieved by sharding data spread across multiple machines instead of scaling up to larger, more expensive servers, MongoDB works, that is. This enables it to scale to huge data volumes and high traffic with the addition of nodes.

3. High Availability Using Replica Sets

Your data is stored multiple times by MongoDB with replica sets. Should the primary fail, a secondary is promoted and the applications continue to run, with minimal disruption.

4. High Performance at Scale

The document model ensures data is stored near each other, avoiding costly joins. Together with in-memory processing and efficient indexing, this provides quick reads and writes on big volumes.

5. Rich Query Language and Aggregation Framework

Unlike early NoSQL systems, MongoDB has plenty of power when it comes to powerful queries, filters, and a rich aggregation pipeline for transforming and analyzing data in the database.

6. Powerful Indexing Options

In addition to basic indexes, MongoDB offers compound, geospatial, and text indexes, enabling you to optimize a diverse range of query patterns, such as location-based and full-text search.

7. Maintainability and Quick Fixes

Documents are naturally mapped to objects that developers play with in the code, thus minimizing the complexity between application and database. The schema can be flexible to allow teams to create and modify features rapidly without intensive data modeling.

Uses Unstructured and Semi-Structured Data

MongoDB is ideal for data with irregular structures, such as user profiles, product catalogs, readings from IoT devices, content, and logs.

Cloud-native with a Managed Option

The managed cloud service, MongoDB Atlas, manages provisioning, scaling, backups and maintenance on major cloud providers, so that teams can concentrate on their application, rather than their database.

When MongoDB Might Not Be the Right Choice

Fit is a part of good architecture – and an honest one. MongoDB is not as well-suited for applications requiring complex multi-table joins or heavy transactional integrity, such as those that involve multiple records — specifically those that feature a well-developed relational database system like Oracle or PostgreSQL.

Many modern systems rely on both: a relational database (for transactional core data) and MongoDB (for flexible, high scale components). Obviously, the correct answer is dependent on the data and access patterns.

Frequently Asked Questions

Which one is better, MongoDB or a relational database?

There is no one ‘right’ answer — it depends on the workload. MongoDB is good at flexible, high-scale unstructured data, while relational databases are better for structured data with complex relationships and strict transactional requirements.

What is the use of MongoDB?

MongoDB is ideal for applications that have dynamic, changing schemas, large volumes of data, or semi-structured data, such as content management systems, real-time data analysis, IoT, catalogues, or backends for mobile apps.

Is there a way to support transactions on MongoDB?

Yes. Although MongoDB has introduced multi-document ACID transactions, it is generally preferable to use relational databases for highly transactional and join-oriented applications.

Choosing the Right Database? Talk to RalanTech

Picking between NoSQL and relational — or combining them — is a decision that shapes your application’s performance and cost for years. RalanTech’s database consulting and database modernization teams help you evaluate, architect, and manage the right data platform for your workload, whether that’s MongoDB, a relational engine, or a hybrid of both. Schedule a free consultation.