TL;DR

Lets take a look at the ecosystem for databases and the tools that govern them.

To note, a database is a collection of inter-related data which helps in efficient retrieval, insertion and deletion of data from database and organizes the data in the form of tables, views, schemas, reports and more.

Looking at what database management systems can do we realize that these tools are used to manage our databases out of the box.

In short, a database management system is the software used to efficiently and reliably handle data processing and management.

Introduction

By the end of this tutorial, you will

• Understand the fundamentals of databases
• Working points of DBMS
• How to run simple Database queries

Core Concepts

We must always be thinking about our data

Quick use cases,

1. Creation of a database
2. Retrieval of information from the database
3. Updating the database
4. Managing a database

With DBMS's being so important in the management of our databases a DBMS will look to focus on the following problems: Redundancy of data, Inconsistency of Data, Difficult Data Access, Unauthorized Access, No Concurrent Access, No Backup and Recovery.

Architecture

The structure of a DBMS is laid out in three levels which are known as your physical, conceptual and external levels. This can be looked at as a 3-tier'd architecture in relation to what a DBMS provides.

Each level will serve a specific focus for a DBMS as the physical layer is the information about the location of database objects in the data store is kept. The conceptual level data is represented in the form of various database tables. At the external level objects will specify a view of the data in terms of conceptual level tables.

As noted earlier, we must always think about our data. This is important walking through the 3-tier architecture as data independence states that changes in data at one level shouldn't affect another.

Types of Data Independence:

1. Physical Data Independence: Any change in the physical location of tables and indexes should not affect the conceptual level or external view of data.

2. Conceptual Data Independence: The data at conceptual level schema and external level schema must be independent.

This concludes the first part of my series on Database Management Systems, I will be posting more on whats to be continued shortly!