NoSQL Databases
NoSQL databases are non-relational databases which allow the user to store data without a defined schema. Generally, NoSQL databases fall into four categories: Key-value stores, Document databases, Wide-column stores, and Graph stores (“What is NoSQL?,” n.d.). While all of these techniques store data in different ways, they all enable the user to large quantities of unstructured or semi-structured data more efficiently than a relational database would allow.
NoSQL relates directly to the material I am currently studying in my Data Analytics class as it, like Comma-Separated Values (CSV) and JavaScript Object Notation, allows the user to store data that does not need to be fully structured efficiently. When information does not have a predetermined structure, NoSQL may be used to store the data. NoSQL differs from SQL as SQL requires the user to define a schema for the database before information can be stored. With NoSQL, the database schema is dynamic and can change as more information is entered.
This technique would be particularly useful in situations where high quantities of data would need to be stored. A notable example of the implementation of NoSQL is Amazon’s DynamoDB, which allows Amazon to use NoSQL to store shoppers’ carts while shopping (Butler, n.d.). Before using DynamoDB, Amazon had to store shoppers’ carts in traditional relational databases which, during peak shopping times, began to cause certain functionalities of their website to crash. NoSQL opened the doors for larger quantities of semi-structured or unstructured data to be stored more efficiently than ever before.
Butler, B. (n.d.). Amazon’s cloud-based DynamoDB helped usher in the NoSQL database market. Retrieved from https://www.networkworld.com/article/2932313/how-amazon-s-dynamodb-helped-reinvent-databases.html
What is NoSQL? (n.d.). Retrieved from https://www.mongodb.com/nosql-inline