Overview

Any modern application, mobile, web or an online service, should be able to store and retrieve data. This task produces a lot of tools, theories andpractices with a single responsibility: data storage.

This course examines the basics of modern database technologies and its use in data-intensive applications. A particular focus on how to choose the right database technology according to tradeoffs between performance, ease of use, data integrity, as well as other considerations will be learned. Hands-on lessons are going to be taught using SQLite, PostgreSQL, MongoDB, Redis and Snowflake databases.

The course starts with a summary of how data storing works for an application. We proceed with a list of essential data storing tool requirements, such as: ACID, transactions, data access languages (SQL). Afterwards, we’ll study classical relational databases (Oracle, MS SQL, PostgreSQL, MySQL). Later, we’ll describe how this century's technological advancements gave birth to a set of non-classical databases, such as: in-memory storage, document storage, columnar storage, etc. The bulk of the remaining course focuses on the tradeoffs to be considered during technology selection and database design. We will emphasize the difference between OLAP (analytical) and OLTP tasks. We’ll spend some time on data modeling for BI and OLTP.

A significant amount of time will be dedicated to the practical skills needed for developers and analysts to work with most of the databases listed above. The course will try to illustrate what type of skills can be useful, regardless of the database selected: SQLite, PostgreSQL, MySQL, Snowflake, CockroachDB or Spanner. The course will illustrate similarities between all the databases and the important differences between them. Practical tasks will help the students develop skills on how to master a new database and discover its capabilities and limitations.