This article is part 1 of the database tutorial.
Here, we cover the following:
This database tutorial is for beginners. It explains basic concepts and assumes no prior knowledge of databases.
You don’t need to follow along – there aren’t any exercises. But there are plenty of screenshots and a few diagrams. The purpose of the tutorial is to introduce you to the basic concepts of databases.
An MPP database is a massively parallel processing database (MPP stands for Massively Parallel Processing).
Massively parallel processing refers to the use of a large number of processors (or separate computers) to perform a set of coordinated computations in parallel (simultaneously).
ORDBMS stands for Object-Relational Database Management System.
An ORDBMS is a database management system that is a hybrid between the object-oriented model (OODBMS) and the relational model (RDBMS).
Each of those two models has their strengths and weaknesses. By combining the two models, a DBMS can take advantage of various strengths from each model.
OODBMS stands for Object-Oriented Database Management System.
An object-oriented database management system (also known simply as an object database) is a DBMS where data is represented in the form of objects, as used in object-oriented programming.
In contrast to relational database management systems (RDBMSs), where data is stored in tables with rows and columns, an object-oriented database stores complex data and relationships between data directly, without mapping to relational rows and columns.
A data warehouse is a large collection of data that can be used to help an organisation make key business decisions.
Here’s a more precise definition of the term, as coined by Bill Inmon, (considered by many to be “the father of data warehousing”):
A data warehouse is a subject-oriented, integrated, nonvolatile, and time-variant collection of data in support of management’s decisions.
The term big data refers to the massive amounts of data – both structured and unstructured – that inundate organisations on a day-to-day basis.
Typically, big data is so large, and accumulates so fast, that traditional data storage and processing applications are inadequate.
The big data industry helps organisations capture and analyse their big data, so that those organisations can make more informed business decisions.
DBMS stands for Database Management System.
A database management system is an application that enables the creation and administration of databases. Database management system is a broad term that includes any system that performs that function.
The most common type of DBMS is an RDBMS (Relational Database Management System). RDBMSs allow you to create relational databases – databases that have multiple tables that contain related data.
Different database management systems define schema in their own way. This can make it difficult for database developers to work out exactly what a schema is – especially when switching between different DBMSs.
This article provides definitions used by the three leading database systems.
In database terms, a schema (pronounced “skee-muh” or “skee-mah”) is the organisation and structure of a database. Both schemas and schemata can be used as plural forms.
A schema contains schema objects, which could be tables, columns, data types, views, stored procedures, relationships, primary keys, foreign keys, etc.
A database schema can be represented in a visual diagram, which shows the database objects and their relationship with each other.
Above is a simple example of a schema diagram. It shows three tables, along with their data types, relationships between the tables, as well as their primary keys and foreign keys.