WhizLabs hosted a webinar with Brian H. Hough, a Cloud and Blockchain Developer as well as an AWS Community Builder. He is currently the Chief Technology Officer at Airblock Technologies and has won five times the Global Hackathon.
He has extensive industry experience and set out to explain AWS Databases to young professionals and freshers. The webinar agenda was as follows:
Overview of AWS Databases
A Brief History of Serverless Databases
Walkthrough of 9 Types Of AWS Databases
Get Started with Your Own App
Brian states that he is passionate about data and databases. He sees data as the energy flowing through a house, while databases are the electrical grid.
Data can refer to the user’s information. It could include a username, password, song title, author, or any other information. You can set up role-based permissions to share certain types data with certain groups. Data is the basis of user interactions. The databases determine what users can do in their accounts as well as in other accounts within the system. Data can also be used to determine the rules that support your software system. This can be back-end logic.
This could explain how the system shares data and how users get recommendations, such as on Netflix. You can see how you get recommendations for movies you’ve watched. When we look at front-end and backend data, everything is moving towards full stack.
This trend has been evident throughout the history and evolution of databases.
Brief History of Databases
1D: Physical Databases
Databases have existed since the invention of the abacus. This was a physical database that had a limitation: it only could process the data the system can process.
2D: Server Databases
Next, the server databases were restricted to specific devices that you need to manage, maintain, and patch to provide updates. It takes a lot of work and requires skilled professionals in both hardware as well as software.
3D: Serverless Databases
This is the moment we move to a three-dimensional space with serverless databases. This allows users to scale their own databases using an OS. This is how AWS created, for instance, a whole ecosystem behind serverless technology – Virtual Private Cloud, Elastic Cloud Compute, and (EC2).
You can now compute network servers but you don’t have to manage them. Other large facilities manage them, which allows you to use a lot of different technologies and servers every day. AWS databases are able to help you manage and allow your own servers. You can also borrow compute from another person.
4D: Data-driven development
Data-driven development is the future. It’s not enough to just make software or apps. You will need to also create a data model to manage data among your users.
Walk-through of 9 AWS Databases Usecases
RELATIONAL DATABASE SERVICE (RDS).
Relational Database Service (RDS), which is quick to set up the framework for a relational AWS data base, can be used with a variety of engines. There are a variety of DB engines available, including Aurora from Amazon, PostgreSQL MySQL, MariaDB and Oracle, as well as SQL Server. They are extremely cost-effective and highly scalable, while still maintaining top security. They allow you to offload read traffic and create and connect to the database in seconds. RDS can be run serverless with a VPC. Brian taught attendees how to create a MySQL Workbench database and gave great tips for beginners. Visit xyz.com to find out more.
DYNAMODB
DynamoDB, one of the most used AWS databases, is fast, flexible, and no SQL database. It allows you to use a primary key for index items and has unique identifiers of all elements in the database. It provides high availability and performance with a single-digit latency. This AWS database is used by top companies such as Lyft and Capital One, Samsung, Toyota, and Airbnb. DynamoDB is specifically designed for developers who need to scale up or down depending on the requirements of their application.
ELASTICACHE
Elasticache is used to deploy and scale in-memory data storage. This can be done serverless by using caching instead of normal, non-performant loading. Caching is a great way to improve performance and response times – operations happen in less than a millisecond. It is an AWS database use case and offers fully managed Redis, Memcached, and other services. This AWS database is an in memory data store and provides low latency for companies such as Tinder, Airbnb, or The Pokemon Company.
NEPTUNE
Neptune is a fully managed graph database service. Graph databases are interrelations between us