Introduction to Databases - Lecture Notes

Instructor

• Jennifer Widom from Stanford University

Overview

• Learning about databases and database management systems (DBMS)
• Emphasis on DBMS from the perspective of the designer, user, and developer

Key Concepts of DBMS

Definition

• Handles large amounts of data
• Provides efficient, reliable, convenient, and safe multi-user storage and access to massive persistent data

Prevalence

• Used in websites, banking systems, telecommunications, sensor deployments, scientific experiments, etc.

Why DBMS are Popular

Ability to Handle Massive Scale

• Terabytes of data, much larger than typical memory

Persistence

• Data outlives the programs operating on it
• Multiple programs can operate on the same data

Safety

• Guarantees data consistency despite failures (hardware, software, power outages) and malicious users
• Built-in mechanisms to ensure data reliability

Multi-user Access

• Mechanisms to ensure data consistency with concurrent users (Concurrency Control)
• Allows multiple users to access data items concurrently without exclusive access

Convenience

• Designed to make working with large amounts of data easy and powerful
• Physical Data Independence: Program operations independent from the data storage layout
• High-Level Query Languages: Declarative, describing what is needed without specifying the algorithm

Efficiency

• Essential for handling thousands of complex queries or updates per second over large datasets

Reliability

• Provides near 100% uptime guarantees for critical applications like banking and telecommunications

Scope of the Course

Exclusions

• Frameworks (e.g., Django, Ruby on Rails) for program development
• Middleware (e.g., application servers, web servers)
• Non-DBMS data storage (e.g., files, Excel spreadsheets)
• Non-DBMS data processing frameworks (e.g., Hadoop)

Focus

• Database management system usage, features, and operations

Key DBMS Concepts

Data Model

• Describes how data is structured
• Examples: Relational data model (records), XML documents (hierarchical structures), Graph data model (nodes and edges)

Schema vs. Data

• Schema: Structure of the database (like types in programming)
• Data: Actual information stored within the schema (like variables in programming)
• Data Definition Language (DDL): Used to set up schema
• Data Manipulation Language (DML): Used for querying and modifying data

People Involved in DBMS

Database Implementer

• Builds the database system (not the course focus)

Database Designer

• Establishes the schema for the database
• Structures complex data for applications

Application Developer

• Builds programs that operate on the database
• Can have multiple programs accessing the database for different functions

Database Administrator

• Loads data and keeps the system running smoothly
• Tunes parameters for optimal performance
• Highly valued and well-paid role for large deployments

Conclusion

• Databases are a fundamental part of everyday life
• Focus on design, development, and administration of database applications in this course