Day 14 of 100 Days of AWS: Database basics part - I

Hi folks! Welcome to Day 14 of 100 Days of AWS🎯, where we will cover the complete AWS cloud from beginner to professional. Today, we will expand our horizons in the AWS cloud by understanding what data is and why it is necessary to store our data in the database and its types. We will also discuss data categories, how the Database Management system concept helps manage data in SQL Databases, and lastly, types of AWS-offered Datastores. Let’s get started🚀!

Day 13 Overview;

On Day 13 of the "100 Days of AWS" series, we focused on understanding the basics of containerization and orchestration in the AWS cloud. Containers are highlighted as tools that package applications with all necessary dependencies, ensuring consistency across environments. The article discusses the challenges of running applications in containers and how container orchestrators like AWS ECS and EKS help overcome these challenges. ECS is described as a simple, fully managed service by AWS, while Kubernetes is an open-source orchestrator offering flexibility and a larger community. EKS combines the benefits of both by managing the control plane, simplifying Kubernetes usage within AWS. The article concludes by emphasizing the importance of choosing between ECS and EKS based on application needs and trade-offs.

What is Data;

In this modern digital world, everything is data, which means that data is the new oil. Data in its raw form is just information with which a user or machine can form meaningful information. such as analysing user information to predict user behaviour in the e-commerce web application, and storing the users shopping cart items. since the data generated by users is increasing exponentially, storing, organizing, and managing large amounts of data becomes crucial. enabling features like data integrity, security, scalability, and easy access for multiple users and applications. which is made possible by storing the data in the database.

What is Database;

Database is an organized collection of structured information or data typically stored electronically in computer system. Together, the data and the DBMS, along with the applications that are associated with them, are referred to as a database system, often shortened to just database.

Data within the most common types of databases in operation today is typically modeled in rows and columns in a series of tables to make processing and data querying efficient. The data can then be easily accessed, managed, modified, updated, controlled, and organized. Most databases use structured query language (SQL) for writing and querying data.

Types of Database;

Database is mainly classified into two types SQL Structured Query Language(SQL), Not only SQL (No SQL)

• SQL

  SQL databases, also known as Relational Database Management Systems (RDBMS), store data in structured tables. They rely on a predefined schema to determine the organisation of data within tables, making them suitable for applications that require a fixed, consistent structure.

  • Structured Data: Data is organized in tables with rows and columns, making it easy to relate different types of information.

  • ACID Compliance: SQL databases follow the ACID properties (Atomicity, Consistency, Isolation, Durability) to ensure reliable transactions and data integrity.

  • Examples: Popular SQL databases include MySQL, PostgreSQL, Oracle, and MS SQL Server.

• No SQL

  NoSQL databases, on the other hand, are designed to handle unstructured or semi-structured data. Unlike SQL databases, NoSQL offers dynamic schemas that allow for more flexible data storage, making them ideal for handling massive volumes of data from various sources.

SQL vs no SQL;

Types of Data;

• Structured Data

  Structured data is data whose elements are addressable for effective analysis. It has been organized into a formatted repository that is typically a database. It concerns all data which can be stored in database SQL in a table with rows and columns. They have relational keys and can easily be mapped into pre-designed fields. Today, those data are most processed in the development and simplest way to manage information. Example: Relational data.

• Semi-Structured Data

  Semi-structured data is information that does not reside in a relational database but that has some organizational properties that make it easier to analyze. With some processes, you can store them in the relation database (it could be very hard for some kind of semi-structured data), but Semi-structured exist to ease space. Example: XML data.

• Un Structured Data

  Unstructured data is a data which is not organized in a predefined manner or does not have a predefined data model, thus it is not a good fit for a mainstream relational database. So for Unstructured data, there are alternative platforms for storing and managing, it is increasingly prevalent in IT systems and is used by organizations in a variety of business intelligence and analytics applications. Example: Word, PDF, Text, Media logs.

Database Management System in general;

A Database Management system is a software solution designed to efficiently manage, organize, and retrieve data in a structured manner. It serves as a critical component in modern computing, enabling organizations to store, manipulate, and secure their data effectively.

from small applications to enterprise systems, DBMS plays a vital role in providing Data-driven decision-making and operational efficiency.

so what is DBMS;

DBMS is a system that allows users to create, modify, and query databases while ensuring data integrity, security, and efficient data access. Unlike traditional file systems, DBMS minimizes data redundancy, prevents inconsistencies, and simplifies data management with features like concurrent access and backup mechanisms.

It organizes data into Tables, views, schemas, and reports providing a structured approach to data management.

Types of AWS offered Datastores (Databases);

AWS offers three types of Datastore for various purpose such as storing application data, Data analysis, Data science, and much more.

• Self Managed Datastore;

  These are the AWS Service option where the customer will launch an ec2 instance and run the database while maintaining the software patches and security configurations are handled by the customer. AWS is only responsible for the underlying physical hardware

• SQL Datastore;

  In Contrast to Self Managed Datastore. SQL datastore is also a Relational SQL database

  where now the software patches replication and everythingise managed by AWS on your behalf. all you have to do is focus in core development logic and customer

• No SQL Datastore;

  NoSQL databases, otherwise known as purpose-built databases, are designed for specific data models and stores data in flexible schemas that scale easily for modern applications. Many database workloads can benefit from the cost-effectiveness and performance of NoSQL databases. As an example, Amazon DynamoDB is serverless so resource utilization is automatically optimized and you never pay for over-provisioning. Moreover, NoSQL databases are widely recognized for their ease of development, functionality, and performance at scale.

Day 14 wrap up;

In conclusion, Day 14 of the "100 Days of AWS" series provided a comprehensive overview of database basics, emphasizing the importance of data storage and management in the digital age. We explored the fundamental concepts of data, databases, and the types of databases, including SQL and NoSQL. Additionally, we delved into the role of Database Management Systems (DBMS) in efficiently organizing and retrieving data. The discussion also highlighted the various types of data, such as structured, semi-structured, and unstructured data, and how AWS offers different datastore options to cater to diverse data management needs. As we wrap up Day 14, we have laid a solid foundation for understanding databases, setting the stage for more advanced topics in the

Summary & Key points;

up next on Day 15;

• Will cover all the individual services offered by AWS in the Database category. and each one’s use case.