Column Stores

Concurrency Control

Crash Recovery

Data Mining

Data Warehousing

Distributed DBMSs

Entity-Relationship Model

External Sorting

File Organizations & Indexing

Hashing

Physical Database Design

Query Optimization

Relational Algebra

Relational Calculus

Relational Model

Relational Operators

Schema Refinement and Normalization

Transaction Management

Tree-Structured Indexes

15-415/615 Database Applications Carnegie Mellon University Fall 2016 This course introduces databases, data models, SQL, database design, query optimization, indexing, and transaction management. It aims to impart understanding of when and how to use database management systems. The course is heavily based on the textbook "Database Management Systems" by Raghu Ramakrishnan and Johannes Gehrke. Course topics:

- Introduction to Databases
- Data Models
- Query Language (SQL)
- Database Design
- Query Optimization & Indexing
- Transaction Management
- Advanced Topics Students will learn the fundamentals of database management systems.

- When to use them
- How to model data with them
- How to store and retrieve information
- How to search quickly for information
- System internals & key algorithms  Raghu Ramakrishnan, Johannes Gehrke, "[Database Management Systems](http://www.amazon.com/Database-Management-Systems-Raghu-Ramakrishnan/dp/0072465638/ref=ed_oe_h)," McGraw-Hill 2002 (3rd ed).


15-415/615 Database Applications

Database systems are modern data storage and processing systems, including relational databases, cluster computing systems, streaming and machine learning systems. Common sub-topics include Data Models, Query Language (SQL), Database Design, Query Optimization & Indexing, etc.

Database Systems

Computer Science

CS 145 Data Management and Data Systems Stanford University Fall 2022 This course primarily focuses on the utilization of databases in applications, scaling for large datasets, and effective data systems design. It explores relational data models, SQL, and schema design, concluding with a hands-on SQL+Python project. The course requires CS 103 and CS 107 or equivalent as prerequisites. This course covers how to use databases in applications, first principles on how to scale for large data sets and how to design good data systems.

A few key topics:

— Introduction to relational data model, relational database engines, and SQL.

— How to scale systems for large data sets on servers and server clusters

— How to design good schemas based on dependencies, normal forms so we build and evolve good applications. This will include indexes, views and transactions.

The class will culminate in a hands-on programming project in SQL+Python — a key part of the course — where you will query, visualize and predict from terabytes of data on [BigQuery](https://cloud.google.com/bigquery/), a popular cloud database part of Google Cloud Platform.  CS 103 and CS 107 (or equivalent) 

CS 145 Data Management and Data Systems

CS 186 Introduction to Database Systems UC Berkeley Spring 2023 This project-heavy course covers access methods, data models, query languages, database services, and interfaces. It introduces transaction processing and requires CS 61A, CS 61B, and CS 61C as prerequisites/corequisites. It suggests proficiency in Java for project work. Access methods and file systems to facilitate data access. Hierarchical, network, relational, and object-oriented data models. Query languages for models. Embedding query languages in programming languages. Database services including protection, integrity control, and alternative views of data. High-level interfaces including application generators, browsers, and report writers. Introduction to transaction processing. Database system implementation to be done as term project.  We will expect students to have taken CS 61A, CS 61B, and CS 61C. CS61A/B will be enforced as a prerequisite, and CS61C will be enforced as a corequisite. This class is project-heavy, and there will almost always be a project assigned to you throughout the semester. Students have noted an increase in difficulty compared to offerings of this course predating Fall 2018. We expect proficiency with Java (around the level taught in CS 61B) in order to work on the projects, with the exception of Project 1. Projects vary in difficulty. You can find more information about them in the Projects section below. There is no required textbook for this class, and we will not be assigning required readings. However, if you would like to use a textbook while in this class, we recommend the following:

- [Database Management Systems](http://pages.cs.wisc.edu/~dbbook/), 3rd Edition, by Ramakrishnan and Gehrke (Former official textbook of this class)

- [Database Systems Concepts](https://www.db-book.com/), 6th Edition, by Silberschatz, Korth and Sudarshan

- [Database Systems: The Complete Book](http://infolab.stanford.edu/~ullman/dscb.html), 2nd Edition, by Garcia-Molina, Ullman, and Widom (Previously used by Prof. Cheung)

Note that exams and all other aspects of the course will center on material as covered in the lectures, so defer to course material if there are any discrepancies with the textbook(s) you are using.

If you want to try to target your reading to the topics of this class, reading assignments from previous offerings of CS 186 for the Database Management Systems textbook can be found [here](https://docs.google.com/spreadsheets/d/1JfrHl8hn8-iMqL2se4SYS0lxQyiwz54YIATFXuzaPlA/edit?usp=sharing). Reading assignments from a database class taught at a different university by Prof. Cheung for Database Systems: The Complete Book can be found [here](https://courses.cs.washington.edu/courses/cse414/18sp/calendar/lecturelist.html), although the topics taught in that class differ from those taught in this class.

CS 186 Introduction to Database Systems

CS 245 Principles of Data-Intensive Systems Stanford University Winter 2022 This course delves into the architecture of modern data storage and processing systems, including databases, cluster computing, and machine learning systems. It covers database architecture, query optimization, transaction management, and parallel processing. CS 145 and CS 161, or equivalent, are expected as prerequisites. This course covers the architecture of modern data storage and processing systems, including relational databases, cluster computing systems, streaming and machine learning systems. Topics include database system architecture, storage, query optimization, transaction management, fault recovery, and parallel processing, with a focus on the key design ideas shared across many types of data-intensive systems.  Students should ideally have taken CS 145 and CS 161. If you haven't taken CS 145, the main thing we assume from it is knowledge of basic SQL syntax; you can also read a [SQL tutorial](https://www.w3schools.com/sql/) to an external site. to learn about this. ### Optional Textbook

[Database Systems: The Complete Book (2nd Edition)](https://www.pearson.com/us/higher-education/program/Garcia-Molina-Database-Systems-The-Complete-Book-2nd-Edition/PGM2429.html), by Garcia-Molina, Ullman and Widom, covers a lot of the technical material in the course and may be helpful as a study guide. We focus on chapters 13-20. We will also cover the material in lectures, but this book is a good source of additional information.

CS 245 Principles of Data-Intensive Systems

15-415/615 Database Applications

Overview

Prerequisites

Learning objectives

Textbooks and other notes

Other courses in Database Systems

CS 145 Data Management and Data Systems

CS 186 Introduction to Database Systems

CS 245 Principles of Data-Intensive Systems

Courseware availability

Covered concepts