Development Database Design & Development Amazon RDS

AWS RDS Databases - Fast Track

Fast-track training to work with relational databases on AWS Cloud using AWS Relational Database Service.
Rating: 4.5 out of 5 (329 ratings)
17,665 students
Created by Siddharth Mehta
English

Learn Amazon Relational Database Service Fundamentals and Concepts
Practice hands-on labs with open source as well as commercial databases
Learn database cost estimation techniques
Configure database instance for high availability and performance

Requirements

  • A computer with admin access and internet connectivity
  • An AWS account to practice labs. Some labs with some specific config may cost a few $$.
  • Basic knowledge of operating AWS Web Console, and AWS Networking Concepts like VPC, Subnet, SecurityGroup, Availabilty Zone etc
  • Experience of working with at least one relational database, and conceptual knowledge of topics like database, tables, replication etc

Description

Hi! Welcome to the AWS RDS Databases - Fast Track Training, the only comprehensive and most impactful course on AWS RDS that is available FREE of Cost. This is the only course you would need to get started with AWS RDS.

This course is taught by an Enterprise Cloud Architect, who leads large teams of junior architects in the real world, who has an industry experience of close to two decades in the IT industry, who is a published author, and leads technology architecture of XXX million dollar projects on cloud for multi-national clients.

This course teaches to work with the following AWS RDS Databases along with its related client tools like HeidiSQL, PgAdmin and Oracle SQL Developer. So if you are new to AWS RDS or are preparing for a quick technical discussion on AWS RDS with very limited time at hand, this is the perfect course for you.

  • MariaDB is one of the most popular database servers in the world. It’s made by the original developers of MySQL and guaranteed to stay open source. Organizations like Wikipedia, WordPress and Google uses MariaDB. It is an enhanced, drop-in replacement for MySQL. MariaDB is used because it is fast, scalable and robust, with a rich ecosystem of storage engines, plugins and many other tools make it very versatile for a wide variety of use cases. MariaDB is developed as open source software and as a relational database it provides an SQL interface for accessing data.


  • PostgreSQL is the one of the world’s most advanced open source and popular database. PostgreSQL runs on all major operating systems, including Linux, UNIX (AIX, BSD, HP-UX, macOS, Solaris), and Windows. It is abbreviated as Postgres because of ubiquitous support for the SQL standard among relational databases.


  • Oracle is a proprietary multi-model database management system from Oracle Corporation. It is a database commonly used for running online transaction processing (OLTP), data warehousing (DW) and mixed (OLTP & DW) database workloads.

This course is composed of almost 90% labs and also covers the fundamental theory of important AWS RDS Concepts with some basic FAQs as well. After pursuing this course, if you have any questions related to the subject or need suggestions about pursuing the next course related to AWS data services, please do not hesitate to contact me.

I hope to see you soon in the class !

Who this course is for:

  • Database professionals who are new to working with databases on AWS Cloud
  • Database Architects who are considering to evaluate relational database capabilities on AWS Cloud for migration
  • Database Developers who want to setup a database on AWS cloud and practice database development

Course content

6 sections • 28 lectures • 2h 15m total length

  • Instructor Introduction
    01:48
  • AWS Data Architecture Landscape and Course Coverage
    05:22
  • Pre-requisites - What you'll need for this course
    02:08

Instructor

Siddharth Mehta
Enterprise Cloud Architect, Published Author, Cloud Geek
Siddharth Mehta
  • 4.4 Instructor Rating
  • 6,954 Reviews
  • 57,404 Students
  • 10 Courses

Udemy's Top 10% of most engaging instructors

My name is Siddharth Mehta. I have career experience of more than 15 years in the IT Industry and am presently working as Enterprise Cloud Architect. I am published author on many online and print-media publications. I have taught thousands of students on Udemy and have number of courses on Data and Analytics. 

Would you consider learning from just any hobbyist who knows programming or someone who just teaches programming without practically using it in the real world, or someone who has experience of using the technology in real world on multi-million dollar large-scale projects globally ? I will teach you everything I know about the subject, from my years of practical experience in the field of BI, Data, Analytics, Cloud and Data Science.

If you are interested in learning more about me, below are some of my career highlights:

I have career experience of more than 15+ years and am presently working in New York Metro region as Enterprise Architect for a life-sciences proprietary multi-tenant product technology portfolio, managing an ecosystem of ISVs and tenants. Below are some of my career highlights:


-|- International experience of working across geographies (US, UK, Singapore) for multi-national clients in Banking, Logistics, Government, Media Entertainment, Products, Life Sciences and other domains

-|- Lead architecture of multi-million dollar portfolios containing apps in Cloud, web, mobile, BI, Analytics, Data warehousing, Reporting, Collaboration, CMS, NoSQL and other categories.

-|- Official inventor of a patented application

-|- Published author/reviewer of whitepapers for Microsoft MSDN Library, Manning publication, Packt publication and others.

-|- Certifications: AWS Certified Solution Architect, TOGAF 9, CITA-F, HCAHD and more


In my present role, I remain responsible for Estimations like AO, IO, SI, IC & Security, Architecture Design, Technology Stack selection, Infra design, 3rd party products evaluation and procurement, and Performance engineering. Hands-On Technology experience of below tech:


-|- OS: Win, Linux

-|- Cloud: GCP, Azure, AWS

-|- Databases: Neo4j, AWS Neptune, Redis, Memcached, MongoDB, Cassandra, HBase, SQL Server, MariaDB, Postgres, Aurora, MySQL, SSAS, AWS Redshift, Google BigQuery, Azure Data Lake, AWS RDS, DynamoDB, Athena, AWS Elasticache

-|- Big Data: Google DataProc, AWS EMR, Kafka, Spark, Hive, Oozie

-|- Search: AWS Elasticsearch

-|- Web: Node.JS, Angular, jQuery, REST APIs, React

-|- ESB/ETL: AWS Lambda, Step Functions, AWS Kinesis, AWS Glue, Mulesoft, SSIS, AWS Data pipeline

-|- Data Science: R , Python, GGPlot 2, Numpy, Seaborn, Pandas, Skikit-learn, Spark ML, Data Mining, Regression & Classification algorithms

-|- Reports / Dashboards : Tableau, Qlikview, SSRS, AWS Quicksight, D3