Introduction to Databases and RDBMS

Introduction to Databases

• A database is an organized collection of data
• A Database Management System (DBMS) is software that controls the creation, maintenance, and use of a database

Relational Databases

• Relational Databases ensure persistent data storage, concurrency control through shared database integration, and a standard model for data management
• Databases store data as tables and rows for organization
• RDBMS have the same basic operations for different vendors, making them easily transferable

Impedance Mismatch

• There is a difference between the relational data model and the in-memory data structures
• Relational data models organize data into tables and rows
• SQL operations use “relations” - a set of tuples
• Each tuple is a set of name-value pairs that cannot contain any structure, such as lists or nested records
• In-memory data structures offer richer structure, requiring translation to a relational representation

Data Structure in Memory

• Different tables in a relational database can be split into many rows from a single data structure in memory

Integration of Applications and Databases

• Databases permit shared data storage between applications
• Downsides include increased complexity and difficulty in maintaining integrity since the application may not be trusted

Service Oriented Architecture

• Requires enhanced interaction protocols between applications and databases
• Web services offer a flexible data structure for communication
• XML and JSON provide richer data structure than SQL

Clustered Databases

• Large data sets emerged in the early 2000s leading to the need for scalability in databases
• "Scale Up" involves bigger machines with increased memory, processors, and disk storage
• "Scale Out" utilizes many small machines arranged in a cluster using commodity hardware
• Relational databases are not designed for clusters, leading to challenges in scalability

Clustered RDBMS

• Clustered RDBMS include Oracle RAC and MS SQL Server
• They share a disk subsystem, which can be a single point of failure
• Sharding the database addresses this by running separate servers for different sets of data

Inspiring Approaches

• Google and Amazon faced similar challenges while running large clusters and working with massive datasets
• Google BigTable and Amazon Dynamo are examples of approaches implemented successfully

NoSQL Databases

• Stands for "Not Only SQL"
• Operates without a schema and works with nonuniform data
• NoSQL databases are more scalable and performance-oriented
• Examples include Redis, Memcached, DynamoDB, MongoDB, and Cassandra

Types of NoSQL Databases

• Key-value store: Simplest form of NoSQL, organized as key-value pairs (e.g., Redis, Memcached, DynamoDB)
• Document store: Stores data in document format (e.g., MongoDB)
• Wide-column store: Data is stored in columns, enabling access to specific columns without allocating memory for irrelevant data (e.g., Cassandra)

This quiz covers the fundamental concepts of databases, including database types, the role of Database Management Systems (DBMS), and the structure of relational databases. Additionally, it addresses the challenges of impedance mismatch between relational models and in-memory data structures. Test your knowledge and understanding of these essential database principles.