Introduction to MongoDB

MongoDB is a popular NoSQL database that can store both structured and unstructured data. Founded in 2007 by Kevin P. Ryan, Dwight Merriman, and Eliot Horowitz in New York, the organization was initially called 10gen and was later renamed MongoDB—a word inspired by the term humongous.

It provides both essential and extravagant features that are needed to store real-world big data. Its document-based design makes it easy to understand and use. It is built to be utilized for both experimental and real-world applications and is easier to set up and simpler to manage than most of the other NoSQL databases. Its intuitive syntax for queries and commands makes it easy to learn.

The following list explores these features in detail:

• Flexible and Dynamic Schema: MongoDB allows a flexible schema for your database. A flexible schema allows variance in fields in different documents. In simple terms, each record in the database may or may not have the same number of attributes. It addresses the need for storing evolving data without making any changes to the schema itself.
• Rich Query Language: MongoDB supports intuitive and rich query language, which means simple yet powerful queries. It comes with a rich aggregation framework that allows you to group and filter data as required. It also has built-in support for general-purpose text search and specific purposes like geospatial searches.
• Multi-Document ACID Transactions: Atomicity, Consistency, Integrity, and Durability (ACID) are features that allow your data to be stored and updated to maintain its accuracy. Transactions are used to combine operations that are required to be executed together. MongoDB supports ACID in a single document and multi-document transactions.
• Atomicity means all or nothing, which means either all operations are a part of a transaction as it happens or none of them are. This means that if one of the operations fails, then all the executed operations are rolled back to leave the data affected by transaction operation in the state it was in before the transaction started.
• Consistency in a transaction means keeping the data consistent as per the rules defined for the database. If a transaction breaks any database consistency rules, then it must be rolled back.
• Isolation enforces running transactions in isolation, which means that the transactions do not partially commit the data and any values outside the transactions change only after all the operations are executed and are fully committed.
• Durability ensures that the changes are committed by the transaction. So, if a transaction has executed then the database will ensure the changes are committed even if there is a system crash.
• High Performance: MongoDB provides high performance using embedded data models to reduce disk I/O usage. Also, extensive support for indexing on different kinds of data makes queries faster. Indexing is a mechanism to maintain relevant data pointers in an index just like an index in a book.
• High Availability: MongoDB supports distributed clusters with a minimum of three nodes. A cluster refers to a database deployment that uses multiple nodes/machines for data storage and retrieval. Failovers are automatic, and data is replicated on secondary nodes asynchronously.
• Scalability: MongoDB provides a way to scale your databases horizontally across hundreds of nodes. So, for all your big data needs, MongoDB is the perfect solution. With this, we have looked at some of the essential features of MongoDB.

  Note

  MongoDB 1.0 was first officially launched in February 2009 as an open source database. Since then, there have been several stable releases of the software. More information about different versions and the evolution of MongoDB can be found at the official MongoDB website (https://www.mongodb.com/evolved).