MongoDB is a NoSQL database system, available for free and based on a document-oriented data model. This system is highly praised for its exceptional query language and quick data access. Unlike conventional relational databases, MongoDB stores data in document collections, managed by the highly efficient C++ programming language. This approach ensures that developers can effortlessly access and manage all data as required.
The History of MongoDB
Back in 2007, Kevin Ryan, Dwight Merriman, and Eliot Horowitz – all entrepreneurs – teamed up and established 10gen. Their main objective was to produce a platform as a service, which was open-source and could rival the currently prevalent solutions such as Heroku, AWS Elastic Beanstalk, and Google App Engine. Essentially, 10gen was interested in presenting an option that would cater to the needs of a wider range of users.
During that same year, the 10gen team went on to devise MongoDB – an innovative NoSQL database technology centred around document orientation.
Understanding the MongoDB Database Architecture
Data in MongoDB is structured as documents and encompasses field key-value combinations. Every document has a unique identifier through the _id field, while other fields may also be present.
Collections in MongoDB are clusters of documents, whereby a substantial amount of data is stored within a single one – this is a unique trait compared to conventional database formats.
Let us delve into additional MongoDB characteristics:
Simplicity has constantly been a defining characteristic of MongoDB, largely because of its sole emphasis on documents. Conventional Relational Database Management Systems (RDBMS) are drawn by the rows and columns model, whereas MongoDB is driven by documents. In other words, individual records may comprise multiple hierarchical relationships, which make it an adaptable platform. Besides, MongoDB does not need a unique schema, which makes it simple to add or delete fields from documents.
Created to be Compact
Developers find MongoDB scalability immensely advantageous. Generally speaking, there are two common approaches to database scaling:
- Vertical scaling – Involves substituting the existing server with a more powerful, resource-heavy server that comes with upgraded RAM and faster CPUs.
- Horizontal scaling – Entails adding supplementary servers to the current one.
MongoDB has a scalable core, simplifying the distribution of data across multiple servers. Developers can take advantage of this feature and other MongoDB tools to redistribute data in a cluster and balance the workload. MongoDB also offers load balancing to redirect updates to their correct destinations.
A Plethora of Features
- Specification of Collection and Index Types
- File Storage Mechanisms
MongoDB boasts of exceptional performance as its underlying function is to generate powerful databases that are versatile, scalable, and lightning-fast.
Why do Developers Prefer MongoDB?
Rapid ExecutionMongoDB is popularly known for its swift performance, thanks to BSON (Binary JSON) document formatting, that accelerates data storage. This fosters denormalization by duplicating data whenever required, resulting in unparalleled efficiency and faster computation rate.
VersatilityMongoDB collections do not follow any specific defined data structure, unlike Structured Query Language (SQL) databases, which grants it the “schemaless” trait. This becomes a valuable aspect in project prototyping phases since the data organisation may still be malleable. The fluidity of data management offered by the absence of a defined schema is an added advantage.
Robust ArchitectureMongoDB furnishes stability and dependability through its use of multiple versions of the database. This double-layered redundancy assures quick access to data, even if there is a system failure. The database replication capability across numerous machines and locations additionally increases database scalability horizontally.
What are MongoDB’s Key Attributes?
BSONBSON refers to binary-encoded serialization of JSON-like documents.
DocumentsMongoDB utilises BSON documents to store data. A MongoDB document is essentially an assemblage of value-and-field pairs.
CollectionsMongoDB sorts documents into collections, which consist of several documents.
DatabasesMongoDB is a database that conserves multiple collections.
NamespaceA namespace is generated when a database collection is linked to a database name. This mechanism aids developers in identifying collections efficiently. For instance, in case the collection name is ‘books’, and the database name is ‘bookdb’, the namespace for the ‘books’ collection would be ‘bookdb.books’.
MongoDB vs. Relational Database Management System (RDBMS)
Moreover, there are several relevant terms that have been defined differently in both databases. For instance, a “Table” in Relational Database Management System (RDBMS) is commonly known as a “Collection” in MongoDB. A “Tuple” in MongoDB equates to a “Document,” and a “Column” in traditional databases equates to a “Field” in MongoDB. Although these parallels exist, there are still notable differences between the two databases. These differences include:
- MongoDB lacks a traditional schema design and is document-oriented. On the other hand, RDBMS has a schema design that depicts the tables and their respective relationships.
- MongoDB’s architecture, which is scalable and flexible, is based on documents. RDBMS, on the contrary, is highly structured and inflexible.
- Thanks to efficient indexing, MongoDB is quicker than RDBMS.
- MongoDB uses a default ‘_id,’ which is a 12-byte hexadecimal integer that guarantees that each document is unique. In contrast, RDBMS does not.
The following scenarios illustrate why developers prefer MongoDB over RDBMS:
- If developers require storing a huge volume of data in tables, MongoDB offers a built-in partitioning and sharding solution.
- Integrating a new column into a Relational Database Management System (RDBMS) can be a complicated process. Conversely, MongoDB does not need a schema. Therefore, it is reasonably easy to include a new field to MongoDB without disrupting existing documents.
MongoDB Language Support
MongoDB is officially supported by a wide range of programming languages, which includes Perl, PHP, Python, C, C++, Rust, C#, Java, Ruby on Rails, Scala, Go, Erlang, and various others. This diverse language compatibility guarantees that businesses and developers can select the optimal language for their projects.
Setting up MongoDB
- Choose your preferred operating system from the available options on https://www.mongodb.org/downloads.
- The instructions can vary based on the operating system you choose; however, all the steps are straightforward and require minimal effort.
Companies That Use MongoDB
Numerous major companies like EA, Cisco, Shutterfly, Adobe, Ericsson, Craigslist, eBay, and Foursquare heavily rely on MongoDB features.
MongoDB is well-known for its numerous features that provide a speedy and dependable database. It is amongst the most popular databases utilized for building web-based applications that require unstructured data storage. Its expandability is hugely appreciated, making it an excellent option for businesses seeking to grow their storage capabilities.
If you intend to develop a clustered application with high performance, MongoDB is a considerable option to consider.
Above all, to design and develop an excellent application, you will need experienced software developers.