RDBMS Overview and Data Storage Methods

A database management system that stores data in a structured format using tables with rows and columns.

Data is collected from various sources using different methods like batch loading or data entry tools.

An RDBMS provides secure and robust storage for data with features like failover protection, ensuring data availability even in case of hardware failures.

RDBMS uses Structured Query Language (SQL) to process data, allowing for complex queries, updates, and data manipulation.

RDBMS offers features like replication and synchronization to distribute data efficiently across multiple users and systems.

RDBMS works with tools like Oracle Forms and Reports to present data in meaningful and visually appealing formats.

RDBMS allows integration with third-party software, enabling the use of data for various purposes like analytics or decision-making.

File-based data management systems were the earliest method for storing data, but have limitations like data redundancy and integrity issues.

A database management system that uses tables with rows and columns to store and organize data, based on relational algebra.

RDBMS was developed as a solution to overcome the limitations of earlier database models like network databases, which were difficult to use and maintain.

RDBMS allows data stored in tables to be independent of the application accessing it, meaning multiple applications can utilize the same data.

RDBMS makes it easier to manage relationships between tables by using a structured approach, unlike older models where changes to relationships could disrupt the entire data structure.

RDBMS utilizes a standardized query language called SQL (Structured Query Language) to interact with and manipulate data stored in tables.

A database model where data is organized in a tree-like structure, allowing one-to-many relationships between parent and child elements. Each child element can only be accessed through its parent node.

A database model where data is organized using pointers, allowing many-to-many relationships between data elements. This eliminates data redundancy by connecting related data directly.

A database model that was developed by IBM in the early 1970s, using keys to locate records quickly. It minimizes input/output operations, making it efficient for data retrieval.

A system where the same data is stored in multiple places, leading to potential inconsistencies and difficulties in maintaining data integrity.

A database concept where data is organized in a strict hierarchy, requiring going through parents to access child nodes. This limitation can create challenges in accessing data directly.

A characteristic of VSAM based systems where data is accessed using unique identifiers called keys. These keys allow for efficient retrieval of specific records.

The concept of having multiple relationships between different data entities in a database. Network databases allow for such complex relationships.

A method used in network databases to connect different data elements together, allowing for efficient data navigation and retrieval.

A database model that stores data in a structured format using tables with rows and columns, enabling complex relationships and data integrity.

Used for immediate user transactions, such as online shopping or entering customer data. Supports high-volume, concurrent access while ensuring consistency.

Used for analyzing large volumes of historical data to identify trends, patterns, and insights. Data is loaded in batches and analyzed for decision-making.

A technique for managing data using a set of predefined rules and procedures, ensuring data consistency, accuracy, and integrity. This includes constraints, referential integrity, and transaction control.