# Different categories of databases exist. Databases in use
# today in business can be broken down into two different categories:
#
# 1. Relational Databases
#
# o These types of databases store information in "tables" that have rows
# and columns of information - very similar to the way the data is
# arranged in an R dataframe.
#
# - Each column of a relational database table
# (a) has a name
# (b) has a datatype (e.g. numeric, logical, character, etc)
#
# - Relational database tables use the term NULL in the same way that
# R uses the term NA - we'll see examples of this later.
#
# o There are MANY different relational database products in use today.
# Some very popular ones are:
#
# - Microsoft SQL Server
# - Oracle Relational Database Management System
# - MySql
# - Postgres
# - MariaDb
# - many, many others
#
# o All Relational database software uses the SQL language to manipulate the
# contents of the database. (there may be a rare exception I don't know about)
#
# Each relational database software product has its own "flavor"
# of the SQL language. You can think of this as different "dialects"
# of the same language. For example the difference between English
# as it's used in the USA vs as it is used in England.
#
# There exists a SQL standard that is recognized by all relational database
# software programs
# (see https://blog.ansi.org/2018/10/sql-standard-iso-iec-9075-2016-ansi-x3-135/#gref).
# However, most relational database products add additional
# capabilities and commands to its version of SQL to differentiate it
# from other relational database products in the market.
#
# In this class we will be focusing primarily on the SQL standard
# features that are included in all relational database products
# and not on the extensions that are provided by the various products.14 “databases” and “database management systems”
“A database” is a collection of data that can be accessed by a computer programs in an accurate and efficient way.
A “Database Management System (DBMS)” is the software that is used to enable the storage and retrieval of the data in a database.
14.1 Different categories of databases
14.1.1 Relational Databases
14.1.2 Non-Relational Databases (AKA NoSQL databases)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# 2. Non-Relational Databases (also known as NoSQL databases)
#
# We will mention more about these types of databases towards the end of
# the semester.
#
# These types of databases organize information in formats other than rows
# and columns.
#
# SOME NoSql databases actually CAN be manipulated with the SQL language.
# However, the term NoSql has come to include any database that stores
# information in a form other than in strict rows and columns.
#
# Some examples are shown below.
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~14.1.3 Graph databases - e.g. Neo4J
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# (a) Neo4J is an example of a "graph database". These types of databases
# organize their information in a structure that looks like a "web"
# of information.
#
# For example see the diagram below
# (For a better version of this diagram see the picture at the top of
# the following webpage: https://aws.amazon.com/nosql/graph/
# or see the file "graph-of-friends.png" file in the files for this lesson.)
#
# (friend)
# Sam <------------ Annie
# ^
# |
# |(friend)
# |
# |
# (friend) | (friend)
# Mac <-------------- Jack ---------------> Doug
# | ^
# | |
# (friend) | |
# | | (friend)
# v |
# Harry Howard
#
# This example shows a set of people and who is friends with whom.
# There is a different icon for each person. "Friend arrows" indicate
# who is friends with whom. In this example the arrows have a direction.
# For example:
# (friends)
# Jack -------------> Doug
#
# can mean that Jack is friends with Doug but Doug is not friends with Jack.
# However, graph databases also have the option to assume that a one-way
# arrow actually implies a two way relationship such that
# Jack ---> Doug also implies that Doug is friends with Jack. In any
# case, this lesson is not focusing on the details of graph databases.
#
# For many types of information a diagram as shown above is much more
# intuitive and understandable than a table of information. This is
# just one reason why graph databases are popular.
#
# However, this same information could be converted to the following
# table and stored in a relational database.
#
# name is_friends_with
# ---- ---------------
# annie sam
# jack annie
# jack mac
# jack doug
# jack harry
# howard jack14.1.4 Document databases - e.g. MongoDB
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# (b) MongoDb is an example of Database Management software that stores information
# in "JSON" notation. We will explore more about JSON later in the semester.
# However as an example, the above information could be represented in a JSON
# file as shown below:
#
# [
# {
# "name" : "annie",
# "friends" : [ "sam" ]
# },
# {
# "name" : "jack",
# "friends" : [ "annie" , "mac" , "doug" , "harry" ]
# },
# {
# "name" : "howard",
# "friends" : [ "jack" ]
# },
# {
# "name" : "sam",
# "friends" : [ ]
# },
# {
# "name" : "mac",
# "friends" : [ ]
# },
# {
# "name" : "harry",
# "friends" : [ ]
# },
# {
# "name" : "doug",
# "friends" : [ ]
# }
# ]
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~