MongoDB Advantages & Disadvantages

MongoDB is a powerful database that’s great at handling lots of data and making sure it’s always available. It uses a flexible way of storing data called documents and collections. As a business grows – it can handle more and more data without slowing down. However, it’s worth noting that MongoDB is licensed under the Server Side Public License (SSPL), which some consider as not entirely free to use, but despite this, it’s widely adopted by companies worldwide across various industries. Its high performance, availability, and scalability make it available for many businesses looking for a robust database engine.

Need of MongoDB

There are lots of reasons to use MongoDB in different applications. Some reasons are the following –

• Versatile Data Management: MongoDB handles both organized and unstructured data across diverse applications. It seamlessly integrates with other popular programming languages and adapts to different tech environments without much effort.

• Robust Query Support: With extensive query capabilities, MongoDB facilitates ad hoc queries. It enables operations such as range queries, field searches, and utilizes regex for precise phrase searches.

• Ideal for Large Data Handling: If your data needs to be stored in tables, MongoDB surpasses traditional RDBMS databases. Its inherent functionalities allow effortless division and distribution of databases, enabling efficient data management.

• Efficient Indexing: MongoDB’s indexing power significantly boosts performance. It allows indexing of any field within a document, elevating the speed and efficiency of search operations. This feature notably enhances the overall search performance of MongoDB databases.

• Supporting Dynamic Schema: In a table, if there are columns for name, address and if we need to enter a new column say “age” in one of the entries — it will not be possible as the column is not defined in the schema. But it can be achieved in MongoDB. Any new field can be inserted regardless of schema . This is known as Dynamic Schema.

Features of MongoDB

MongoDB offers several key features that make it a popular choice among developers and organizations:

• Ad-hoc Queries: MongoDB supports dynamic ad-hoc queries for real-time analytics. It allows developers to execute variable-based queries. This flexibility in querying enables improved performance and real-time updates.

• Indexing for Performance: Proper indexing boosts query execution speed. MongoDB offers diverse indices supporting complex data access patterns and allows dynamic index creation to adapt to evolving query needs.

• Replication: MongoDB’s replica sets ensure data availability by maintaining multiple servers with the same data. It prevents single points of failure, supports disaster recovery, and aids load balancing.

• Sharding: For large datasets, sharding splits data across multiple distributed collections (shards) to improve query execution and scalability. It enables horizontal scaling, essential for handling growing applications.

• Load Balancing: MongoDB’s horizontal scaling capabilities via replication and sharding contribute to efficient load balancing. It manages concurrent read/write requests effectively without needing external load balancers, ensuring consistent data access for users.
• Aggregation Framework: MongoDB provides an extensive aggregation framework that allows for the processing of data and performing aggregation operations such as grouping, filtering, and transformation within the database.
• Schema Evolution: Its flexible schema design allows easy updates and modifications to the database schema without downtime or complex migration procedures, facilitating agile development.

Applications of MongoDB

MongoDB’s flexibility and scalability make it suitable for a diverse range of applications.

• Web Applications: MongoDB’s schema flexibility gives many advantages in web development. MEAN or MERN stack, which includes MongoDB as its database, is quite popular for building robust and scalable web applications.

• E-commerce: MongoDB’s flexible schema and ability to handle varied data types make it suitable for managing product catalogs, user shopping carts, and other applications. The ability to handle interactions between user shopping carts and inventory via Inventory Management makes it a strong choice for e-commerce platforms.

• Big Data & Sharding: MongoDB can handle large volumes of data efficiently and is used in scenarios where big data is generated rapidly and needs to be accessed in real-time. It is capable of scaling horizontally (sharding) to accommodate growing data volumes.

• Demographic and Biometric Data: MongoDB’s scalability and performance makes it suitable for storing massive amount of data. So, it can be used to store demographic and biometric information, like in Aadhar, managing data for over a billion people.

• Synchronization: Its capability to handle synchronization requirements makes it suitable for gaming applications where real-time data updates and interactions are crucial. The use of MongoDB by gaming studios like EA for games like FIFA demonstrates its applicability in this domain. It manages complex game data structures, player profiles, and in-game interactions efficiently.

Advantages of MongoDB

MongoDB has many advantages which makes it popular and highly demanded.

• Schema Not Required: MongoDB doesn’t demand predefined schemas, but schema migration might be necessary for evolving data structures. However, it offers more flexibility than traditional relational databases that strictly require schemas.

• Document Queries: MongoDB’s document-oriented approach aligns with dynamic queries. It allows flexible and varied query operations based on the nature of the documents, unlike static table-based queries of RDBMS.

• Simplified Performance Optimization: Compared to relational databases, MongoDB’s performance optimization is comparatively simpler due to its architecture and the way it manages data internally.

• Efficient Memory Utilization: MongoDB uses internal memory for data storage. So, it accesses the data very fast and enhances the overall performance.

• Horizontal Scaling with Sharding: Using MongoDB, we can horizontally expand our database by distributing data across multiple servers. It is called Sharding. Sharding ensures data separation and even distribution across shards, which is very efficient for data retrieval.

• Ease of Maintenance: MongoDB is generally considered easier to maintain than traditional databases due to its flexible schema and simpler optimization processes.

• Replication and Workload Distribution: By making copies of data and spreading the work across different parts, MongoDB ensures that the information is always available and the system works really fast. This happens because the tasks are shared among many places instead of just one, which makes things quicker and more reliable.

Disadvantages of MongoDB

Despite MongoDB’s many strengths, it also carries a few drawbacks that warrant consideration. Some drawbacks are:

• Limited Transactions Scope: In MongoDB, transactions work within each piece of data (called a document), but they don’t fully cover situations where you need to do multiple things at once across lots of data. This might be tricky for applications that really need everything to happen perfectly together.

• Lacks in Full ACID Compliance: While MongoDB offers Atomicity, Consistency, Isolation, and Durability (ACID) at the document level, it doesn’t provide full ACID compliance across multiple documents or collections. This limitation can be challenging for applications requiring strict and complex transactional guarantees.

• Limited Join Capabilities: Unlike traditional relational databases, MongoDB doesn’t support joins in the same way. While it’s possible to manually perform join-like operations using code, it can slow down execution and affect performance.

• Data Redundancy and Memory Usage: MongoDB stores key names with each value pair, causing some data redundancy due to the limitations of joins. This redundancy might lead to increased memory usage compared to what’s strictly necessary.

• Document Size Limit: MongoDB imposes a maximum document size limit of 16 MB. Larger documents might need to be handled differently or divided into smaller documents to fit within this constraint.
• Nested Document Levels: Document nesting in MongoDB is possible but limited to a maximum of 100 levels. This restriction can impact how deeply you can organize and structure your data within documents.

Conclusion

MongoDB is like a special toolbox for organizing information in a flexible way. It works across different machines and can handle various types of tasks, like managing websites, games, online stores, and more. It is widely scalable with various programming languages, which makes it easier for developers to use. For instance, if a project requires very specific instructions or involves doing many complex things together, MongoDB might not be the best choice. However, it is possible to use MongoDB to support content management systems, online and offline gaming apps, e-commerce systems, mobile applications, data analytics sections, archiving, logging etc.

Overall, MongoDB is a good NOSQL database system for unstructured, complex, and large amounts of data because it can handle all things in an easy manner. But if a project needs super strict rules or involves lots of complicated connections between things, other databases might be better. MongoDB is still a popular choice because it’s useful for many different jobs, even though it might not be perfect for everything.