Course Description
Professionals will learn about the process of planning & designing both relational & non relational databases. Professionals will learn the design considerations for hosting databases on Amazon Elastic Compute Cloud (Amazon EC2). Professionals will learn about our relational database services, including Amazon Relational Database Service (Amazon RDS), Amazon Aurora, & Amazon Redshift. Professionals will also learn about our nonrelational database services, including Amazon DocumentDB, Amazon DynamoDB, Amazon ElastiCache, Amazon Neptune, & Amazon QLDB. By the end of this course, professionals will be familiar with the planning & design requirements of all 8 of these AWS database services, their pros & cons, and how to know which AWS database service is right for your workloads.
Prerequisites
We recommend that attendees of this course have-
- Familiarity with AWS Database Services, equivalent to AWS Database Offerings digital training
- Understanding of database design concepts, &/or data modeling for relational or non relational databases
- Familiarity with cloud computing concepts
- Familiarity with general networking & encryption concepts
- Understanding of the three V’s of data (volume, velocity, & variety)
- Familiarity with basic data analytics concepts, equivalent to Data Analytics Fundamentals digital training
- Understanding of general architecting best practices & the AWS Well-Architected Framework, equivalent to Architecting on AWS classroom training
Target Audience
This course is intended for-
- Data Engineers who are new to designing cloud databases or non relational databases
- Solutions Architects who are designing services or architectures that are integrated with databases
- Developers that are building cloud database-enabled applications
Course Objectives
In this course, professionals will-
- Apply database concepts, database management, & data modeling techniques
- Evaluate hosting databases on Amazon EC2 instances
- Evaluate relational database services (Amazon RDS, Amazon Aurora, & Amazon Redshift) and their features
- Evaluate non relational database services (Amazon DocumentDB, Amazon DynamoDB, Amazon ElastiCache, Amazon Neptune, & Amazon QLDB) and their features
- Examine how the design criteria apply to each service
- Apply management principles based on the unique features of each service
Content Outline
- Databases in the cloud
- Database design principles
- Transactional compliance
- Workload requirements
- Design considerations
- Module 3- Databases on Amazon EC2
- Amazon EC2 for hosting databases
- The journey to AWS
- Data modeling basics
- Module 5- Databases on Amazon RDS
- Amazon RDS databases
- Amazon RDS distinguishing features
- Amazon RDS Design considerations
- Lab 1- Working with Amazon RDS databases
- Amazon Aurora databases
- Aurora distinguishing features
- Aurora design considerations
- Amazon DocumentDB
- Amazon DocumentDB design considerations
- Lab 3- Working with Amazon DocumentDB databases
- Amazon DynamoDB
- DynamoDB data modeling
- DynamoDB distinguishing features
- DynamoDB design considerations
- Lab 4- Working with Amazon DynamoDB Tables
- Amazon Neptune
- Neptune design considerations
- Amazon ElastiCache
- ElastiCache for Memcached
- ElastiCache for Redis
- Amazon Redshift
- Amazon Redshift distinguishing features
- Amazon Redshift data modeling
- Amazon Redshift design considerations
- Lab 5- Working with Amazon Redshift Clusters
- Amazon Quantum Ledger Database (Amazon QLDB)
- Amazon QLDB Design Considerations
- Amazon ElastiCache
- ElastiCache for Memcached
- ElastiCache for Redis
- Amazon Redshift
- Amazon Redshift distinguishing features
- Amazon Redshift data modeling
- Amazon Redshift design considerations
- Lab 5- Working with Amazon Redshift Clusters
FAQs
Amazon Relational Database Service. Amazon RDS is available on numerous database instance types: optimized for memory, performance, or I/O, & provides you with 6 familiar database engines to choose from, including MariaDB, MySQL, PostgreSQL, Oracle Database, Amazon Aurora, & SQL Server.
AWS fully managed database services provide continuous monitoring, self-healing storage, & automated scaling to help you focus on application development. Achieve performance at scale.
A data lake is a centralized & secured repository that collects all your data, both in its original form & prepared for analysis.
There are three methods of data storage, namely –
- Object storage
- File storage
- Block storage
EC2 is a service that enables business clients to run application programs in the computing environment.
AWS security provides opportunities to protect the data, check out security-related activity & receive automated responses.
Radiant believes in a practical & creative approach to training & development, which distinguishes it from other training & development platforms. Moreover, training courses are undertaken by some of the experts who have a vast range of experience in their domain.
Radiant team of experts will be available by email at support@radianttechlearning.com to answer your technical queries even after the training program.
Yes, Radiant will provide you most updated, high, value & relevant real-time projects & case studies in each training program.
Technical issues are unpredictable & might occur with us as well. Participants have to ensure that they have access to the required configuration with good internet speed.
Radiant Techlearning offers training programs on weekdays, weekends & combination of weekdays & weekends. We provide you with complete liberty to choose the schedule that suits your needs.