Introduction to NoSQL
NoSQL is a database that helps manage huge sets of unstructured data, and this data is not stored in tabular relations like in a Relational Database. The majority of existing Relational Databases fail to solve some of the complex modern problems such as:
- Continuously changing nature of data – structured, semi-structured, unstructured and polymorphic data.
- Applications serving millions of users in different geo-locations and time zones need to be up and running all the time while maintaining data integrity
- Applications are becoming more distributed with many moving towards cloud computing.
Structured data is usually text files, with defined column titles and data in rows. Such data can easily be visualized in the form of charts and can be processed using data mining tools.
Unstructured data can be anything like a video file, image file, PDF, Emails, etc. as more and more modern data is unstructured, and there was a need to have something to store such data for growing applications, hence setting the path for NoSQL like MongoDB.
What is MongoDB?
MongoDB is a cross-platform document-oriented database program. It is classified as a NoSQL database program and uses JSON-like documents with schemata. MongoDB is an open source DBMS and is fast and scalable. Unlike relational databases that use tables and rows, MongoDB architecture is made up of collections and documents.
How MongoDB is different from RDBMS
While in RDBMS, a database has a typical schema design that shows the number of tables and the relationship between these tables, while in MongoDB there is no concept of relationship.
MongoDB and RDBMS Databases also differ in the way they handle data. While RDBMS databases store data in a 2-dimensional row-column structure, MongoDB stores data in the form of a rich data document, allowing users to store any type of data.
MongoDB Documents are a form of JSON, thus they are in-line with the structure of objects in modern programming languages. Developers can easily map the data used in the application to its associated document in the database. In RDBMS Database, on the other hand, creating a table with columns mapped to the attributes of an object in a programming language is a little slow and becomes monotonous after some time.
- MongoDB is schema-less and a document-oriented database in which one collection holds different documents
- There may be a difference in the number of fields, content, and size of the document
- Structure of a single object is clear in MongoDB
- There are no complex joins in MongoDB
- MongoDB provides the facility of deep query because it supports powerful dynamic query on documents
- It uses internal memory for storing working sets, which results in faster processing
- As it is a NoSQL database, it is highly secure because it can make SQL injection
- It can also be used as a file system, which in turns helps in easier load balancing
- MongoDB supports Sharding, which is the process of storing the data in different machines to support deployments with very large data sets and high throughput operations
- Performance tuning in MongoDB is very easy compared to any relational databases
Application of MongoDB
- Big and complex data management
- Mobile and social infrastructure
- Content management and delivery
- User data management
- Data hub
- Unstable schema
- Location-based data
- An unstable environment with the need for high availability
In the End
MongoDB comes with a vast list of distinctive features, which includes managing higher write load, faster processing, and usability over RDBMS. This makes it one of the most preferred databases with the biggest corporations in the world. Its set of features enable enterprises to parse all that unstructured data including videos, images, and pdf files. Integrating MongoDB in your business proceedings will eliminate the need for any other database.
That is it from us on MongoDB and its advantages over RDBMS. If we have missed something, do let us know in the comments below.
Until next time!