MongoDB: An introduction

MongoDB is the most popular NoSQL open source document-oriented database. The term 'NoSQL' means 'non-relational'. This means that MongoDB is not based on a table like relational database structure but provides an altogether different mechanism for storage and retrieval of data. This format of storage is called BSON ( similar to JSON format). 

• SQL databases store data in tabular format. These data are stored in a predefined data model which is not flexible for highly growing applications in today's real world.
  
• Modern applications are more social, interactive and networked than ever. Applications stores more and more data and accessing them at higher rates.
  
• Relational Database Management System is not the correct choice when it comes to handle big data by the virtue of their design since they are not horizontally scalable. If the database runs on a single server, then it will reach a scaling limit.
  
• NoSQL databases are more scalable and provide superior performance. MongoDB scales by adding more and more servers and increases productivity with its flexible document model.

A simple MongoDB document Structure: 

{
  title: 'Geeksforgeeks',
  by: 'Harshit Gupta',
  url: 'https://www.geeksforgeeks.org',
  type: 'NoSQL'
}

MongoDB database features

• Document Oriented: MongoDB stores the main subject in the minimal number of documents and not by breaking it into multiple relational structures like RDBMS. For example, it stores all the information of a computer in a single document called Computer and not in distinct relational structures like CPU, RAM, Hard disk etc.
  
• Indexing: Without indexing, a database would have to scan every document of a collection to select those that match the query which would be inefficient. So, for efficient searching Indexing is must and MongoDB uses it to process huge volumes of data in very less time.
  
• Scalability: MongoDB scales horizontally using sharding (partitioning data across various servers). Data is partitioned into data chunks using the shard key and these data chunks are evenly distributed across shards that reside across many physical servers. Also, new machines can be added to a running database.
  
• Replication and High Availability: MongoDB increases the data availability with multiple copies of data on different servers. By providing redundancy, it protects the database from hardware failures. If one server goes down, the data can be retrieved easily from other active servers which also had the data stored on them.
  
• Aggregation: Aggregation operations process data records and return the computed results. It is similar to the GROUPBY clause in SQL. A few aggregation expressions are sum, avg, min, max, etc.

Where do we use MongoDB?

MongoDB is preferred over RDBMS in the following scenarios:

• Big Data: If we have huge amount of data to be stored in tables, think of MongoDB before RDBMS databases. MongoDB has built-in solution for partitioning and sharding our database.
  
• Unstable Schema: Adding a new column in RDBMS is hard whereas MongoDB is schema-less. Adding a new field does not effect old documents and will be very easy.
  
• Distributed data Since multiple copies of data are stored across different servers, recovery of data is instant and safe even if there is a hardware failure.

Language Support by MongoDB

MongoDB currently provides official driver support for all popular programming languages like C, C++, Rust, C#, Java, Node.js, Perl, PHP, Python, Ruby, Scala, Go and Erlang.

Installing MongoDB

Just go to http://www.mongodb.org/downloads and select your operating system out of Windows, Linux, Mac OS X and Solaris. A detailed explanation about the installation is provided.

For Windows, a few options for the 64-bit operating systems drops down. When you are running on Windows 7, 8 or newer versions, select Windows 64-bit 2008 R2+. When you are using Windows XP or Vista then select Windows 64-bit 2008 R2+ legacy.

Conclusion

• MongoDB's document-oriented structure, scalable architecture through sharding and robust features like indexing and aggregation.
• It is a preferred choice for modern applications handling large volumes of data.
• Its ability to manage distributed data effectively and support a wide array of programming languages, MongoDB continues to empower developers to build scalable and efficient applications.