assignment and database algorithmno 4.pptx
- 1. Assignment no.4 Topic:Models of databases Submitted by: Name:waqas Nadeem Semester:AF-2 Subject:Introduction to computer and technology Submitted to: Sir kamran
- 2. Models of Databases: 1.Relational Model: • Structure: Data is organized into tables (or relations) consisting of rows and columns. • Example Systems: MySQL, PostgreSQL, Oracle, Microsoft SQL Server. • Key Features: Uses SQL (Structured Query Language) for querying and managing data. Each table has a unique key and relationships between tables are established through foreign keys. 2.Hierarchical Model: • Structure: Data is organized into a tree-like structure where each record has a single parent and potentially many children. • Example Systems: IBM Information Management System (IMS). • Key Features: Good for representing one-to-many relationships, such as organizational structures or file systems 3.Network Model: • Structure: Similar to the hierarchical model but allows each record to have multiple parent and child records, forming a graph structure. • Example Systems: Integrated Data Store (IDS), Integrated Database Management System (IDMS). • Key Features: More flexible than the hierarchical model, allowing more complex relationships. 4.Object-Oriented Model: • Structure: Data is represented as objects, similar to object-oriented programming. • Example Systems: ObjectDB, db4o. • Key Features: Supports inheritance, polymorphism, and encapsulation. Suitable for applications requiring complex data representations.
- 3. 5.Document Model: • Structure: Data is stored in documents, typically in JSON, BSON, or XML formats. • Example Systems: MongoDB, CouchDB. • Key Features: Schemaless, allowing flexible data structures. Ideal for applications with evolving data models. 6.Columnar Model: • Structure: Data is stored in columns rather than rows. • Example Systems: Apache Cassandra, HBase. • Key Features: Optimized for read-heavy operations, such as analytics and reporting, providing efficient data compression and retrieval. 7.Key-Value Model: • Structure: Data is stored as key-value pairs. • Example Systems: Redis, Amazon DynamoDB. • Key Features: Highly performant for simple lookups, suitable for caching and real-time applications. 8.Graph Model: •Structure: Data is represented as nodes (entities) and edges (relationships). •Example Systems: Neo4j, ArangoDB. •Key Features: Excellent for traversing relationships and finding patterns, used in social networks, fraud detection, and recommendation systems. THE END