Introduction

In this class, we will learn

• How to model and design good databases
• How to store and manage data
• How to query data
• How to reason about query performance
• How to update data

Always ask questions!

• There are no stupid questions (supposedly)

Big data

• Exponential data growth requires efficient database systems
• “Every two days we generate as much data as we did since the dawn of humanity until 2003.” -Eric Schmidt, 2010
• 5 Vs
  • Volume (size)
  • Velocity (rate)
  • Variety (sources)
  • Veracity (accuracy)
  • Value (utility)

Databases

• Model real life data
• Include entities and relationships
• A sophisticated piece of software, used to deal with data efficiently
• “Relational databases are the foundation of western civilization” -Bruce Lyndsey

Database management systems

• Always answer queries in well-defined, consistent ways
• Have mechanisms for handling power outages, concurrency

Data model

• A collection of concepts describing data
• They can be relational, key-value, graphs, time series, documents
• Relational data models are the most commonly used
  • Relations exist through tables
  • Schema describes the columns of each table

Abstraction

• The users view data through external schemas
• Underlying any external schema is an internal, conceptual schema
• Underneath this, the data is physically stored
• Data should have logical data independence and physical data independence

SQL

• Structured Query Language
• A very powerful declarative language

Query semantics

• Atomicity - executed entirely or not at all
• Consistency - leaves DB in a consistent state
• Isolation - behaves as if it is executed alone (even if queries are actually interleaved)
• Durability - once completed, is never lost

Link to original