Database Management System – Week 1: Introduction to Database

Vocabulary flashcards covering fundamental terms, components, architectures, models, users, and challenges introduced in Week 1 Module 1: Introduction to Database.

Data

Raw facts, figures, values, and observations that have not yet been processed for meaning.

Information

Processed data that is meaningful and useful for decision-making.

Database

An organized collection of interrelated data designed to record, maintain, and retrieve large amounts of information efficiently.

Database Management System (DBMS)

Software suite that creates, accesses, manages, and controls databases while acting as an interface between them and application programs.

Relational Database Management System (RDBMS)

Type of DBMS that stores data in two-dimensional tables (relations) and uses Structured Query Language (SQL) for manipulation.

Object-Oriented Database Management System (OODBMS)

DBMS that stores data as objects with attributes and methods, allowing complex data types such as images, audio, and video.

Object-Relational DBMS (ORDBMS)

Hybrid DBMS combining relational tables with object-oriented features to handle complex data while retaining SQL support.

File System

Traditional method of storing electronic data as independent flat files with no built-in relationships or advanced querying.

Flat File

Single, standalone file in a file system that contains rows of data without structured links to other files.

Master File

Relatively static file that stores core reference data, e.g., Employee-Master or Account Holder records.

Transaction File

File that records day-to-day activities or events, such as deposits or loan releases, and is updated frequently.

Table File

Periodically updated file that holds structured data similar to a database table; updated less often than transaction files.

Data Redundancy

Unnecessary duplication of data in multiple locations, often leading to storage waste and integrity issues.

Data Inconsistency

Condition where duplicated data values disagree because not all copies were updated uniformly.

Concurrent Access

Capability that allows multiple users to read or modify data simultaneously for improved performance.

Data Recovery

Processes and on-disk structures that restore a database to a consistent state after failure.

Hierarchical Database Model

Early database model that organizes records in a tree-like parent-child structure with one-to-many links.

Network Database Model

Model extending the hierarchical approach by permitting each record to have multiple parents, enabling many-to-many paths.

Relational Database Model

Model representing all data as simple tables with rows (tuples) and columns (attributes).

Object-Oriented Database Model

Model that stores data as objects containing both state and behavior, mirroring object-oriented programming concepts.

Data Model

Overall logical structure that defines how data is organized, stored, and manipulated in a DBMS.

One-Tier Architecture

DBMS architecture where presentation, business logic, and database all reside on a single machine.

Two-Tier Architecture

Architecture separating the presentation layer (client) from combined business logic and database layers (server).

Three-Tier Architecture

Architecture that isolates presentation, business logic, and database tiers on separate systems for scalability and security.

ODBC (Open Database Connectivity)

Standard API that enables client applications to communicate with various DBMSs in a two-tier setup.

Internal Schema

Physical level description of how data is actually stored on disk, including access paths.

Conceptual Schema

Logical level definition of the entire database structure and constraints, independent of physical details.

External Schema (View)

User-specific subset of the database that provides a customized perspective for simplified interaction.

Physical Level

Lowest abstraction level detailing the physical storage of data.

Logical Level

Middle abstraction level describing what data is stored and relationships among data.

View Level

Highest abstraction level showing only portions of the database relevant to particular users.

Query Processor

DBMS component that parses, optimizes, and executes database queries.

DDL Interpreter

Part of the query processor that interprets Data Definition Language statements and updates the data dictionary.

DML Compiler

Module that translates Data Manipulation Language statements into low-level execution plans.

Query Optimization

Process of selecting the most efficient execution plan among alternatives for a given query.

Query Evaluation Engine

Runtime component that carries out low-level instructions produced by the DML compiler.

Storage Manager

Subsystem that interfaces between low-level stored data and higher-level DBMS components, handling retrieval and updates.

Authorization and Integrity Manager

Storage-manager module enforcing user privileges and database integrity constraints.

Transaction Manager

Component ensuring atomicity, consistency, isolation, and durability (ACID) properties during concurrent operations and failures.

File Manager

Module that allocates disk space and manages on-disk data structures for files and indices.

Buffer Manager

In-memory cache manager that decides which disk pages to load, retain, or evict for efficient I/O.

Index

Auxiliary data structure that speeds up retrieval of rows with specific attribute values.

Data Dictionary

Repository of metadata describing database schemas, tables, columns, and constraints.

Database Administrator (DBA)

Person or team responsible for selecting hardware/software, managing security, integrity, recovery, and performance tuning.

Naive User

End user who interacts with the database indirectly through predefined application programs (e.g., bank teller).

Application Programmer

Professional who writes application software or forms, often using 4GL or RAD tools linked to the DBMS.

Sophisticated User

Analyst who interacts with the DBMS by submitting ad-hoc queries through query languages or OLAP tools.

Specialized User

User who develops non-traditional database applications such as knowledge bases or multimedia systems.

Data Security (Challenge)

Protecting databases from unauthorized access or breaches, a growing issue with publicly exposed systems.

Performance (Challenge)

Need for high-speed data processing despite increasing data volumes and limited hardware.

Data Safety (Challenge)

Guaranteeing that no data is lost and that transactional integrity is preserved.

Resource Utilization (Challenge)

Maximizing the efficiency of available computing resources to handle complex, large-scale data.

High Availability (Challenge)

Ensuring the database remains operational and accessible even if individual servers fail through clustering or replication.