• Online, Self-Paced
Course Description

NoSQL databases are increasingly used in real-time web applications and big data. They provide a mechanism for retrieval and storage of data other than relational databases. They are attractive to developers due to their horizontal scaling, simplicity of design, and finer control over availability. In this course, you'll learn about the fundamentals of NoSQL data stores, the importance of queries and updates, and why a NoSQL implementation may be a better choice than a traditional relational database model.

Learning Objectives

Introduction to RDBMS

  • start the course
  • describe a relational database management system
  • describe SQL
  • recognize situations in which SQL is used

Introduction to NoSQL

  • describe the basic structure of NoSQL
  • identify some of the traits of NoSQL systems
  • identify some of the key points of NoSQL systems
  • recall the four most common categories of NoSQL systems
  • recall some of the major milestones in the NoSQL development process
  • recognize the importance of queries versus updates
  • recognize characteristics that would make NoSQL a better choice than RDBMS
  • define BASE

Implementations of NoSQL

  • describe the four basic ways systems are distributed
  • identify considerations that could be problematic for distributed systems
  • identify considerations for the different types of distributed systems
  • describe consistent hashing and how it can be used
  • describe the fundamentals of big data
  • identify how big data analytics are used

NoSQL Concepts

  • define CAP and Brewer's theorem
  • identify the various implications of CAP
  • define SPRAIN
  • define eventual consistency
  • describe the MapReduce concept
  • describe how MapReduce is used in practice

Practice: Fundamentals of NoSQL

  • describe NoSQL features

Framework Connections

The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):

Specialty Areas

  • Data Administration
  • Systems Administration