Database Systems - Intro to Big Data and NoSQL Key-Value Pair Databases - APPFICIAL

Transactional data is structured data such as student records, financial records, hotel reservations, or sales transactions. Transactional data typically requires a
stable schema – little changes in database structure
vertical scaling - increasing database size, or computer space if database grows
Strict Transaction requirements – follow the ACID properties
Limited replications – Data is replicated in the case of failures, but at the cost of performance
Partitioning - splits big tables into separate physical files on one machine
Rapid nsert, update or deletes

Big data refers to massive complex structured and unstructured data sets that are rapidly generated and transmitted from a wide variety of sources, such as the Internet or mobile apps. There is much more big data than transactional data, and it also comes in at a much faster rate. There is also lots of variety of big data, and much of it comes from the general public in addition to organizations.

Big data requires:
- Flexible schema – data structures vary and can be complex
Horizontal scaling – instead of getting a bigger machine, just get more machines
Less transaction requirements - ACID requirements are more relaxed. For example, some queries against a replica may be out of date and its ok.
Sharding. – used to split up a large data set across multiple machines
Rapid inserts and analysis – fast inserts are needed to accommodate the large amounts of data coming in

NoSQL databases

Relational databases systems were not initially designed for big data causing many non-relational systems to become popular. The most popular type of non-relational systems is called a  NoSQL database, which stores data as key-value pairs, typically in-memory, and is optimized for big data. Although the name noSQL suggests that it doesn’t support SQL, most NoSQL databases have added support for SQL, so noSQL now means 'not only SQL’.

Four major types of NoSQL databases exist:

Key-value databases – a key refers to one value (like a dictionary)
Wide column databases – key refers to a value, which can be multiple values, or multiple database columns
Document database – key refers to a value, which is a document like JSON or XML
Graph database – The data is a graph with nodes and edges

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