Overview

The course examines the basics of modern database technologies, from the point of view of database developer and analyst, and its usage for data-intensive applications. A particular focus is given to choosing the right database technology for a task at hand and tradeoffs between performance, ease of use, data integrity and other considerations. Hands-on lessons are done using SQLite, PostgreSQL, MongoDB, Redis and Snowflake databases.

The course starts with a brief overview of a data storing task for an application. We proceed with a list of requirements, which proved to be essential for a data storing tool: ACID, transactions, availability of data access languages (SQL, etc.). Afterwards, we will illustrate why given requirements determined the market dominance of classical relational databases (Oracle, MS SQL, PostgreSQL, MySQL, etc.) at the end of the 20th century. Later we describe why technological advances of the 21st century 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 the database design. We emphasize the difference between OLAP (analytical) and OLTP tasks and modern data warehouse designs (Data Vault, Anchor Modeling, etc.).

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