Presentation1_datascience_tybca_bcs.pptx

Just related to syllabus

1. 1) Key Value Database Description: Store data as a collection of key-value pairs. They are highly performant and scalable, suitable for use cases requiring fast retrieval. Use Cases: Often used for caching, session management, and real-time data analysis. Here are five concise points: Simple Data Model High Performance Scalable Flexible Schema Eventual Consistency

2. 2) Column Oriented Database Description: Store data in columns rather than rows, allowing for efficient data compression and retrieval. Each column family is akin to a table but can have a dynamic schema. Use Cases: Suitable for large-scale data warehouses, big data analytics, and applications with large volumes of write-heavy transactions. Points about column-family stores: Columnar Storage Flexible Schema High Scalability Efficient Queries Eventual Consistency

3. 3) Graph Database Description: Designed to represent data in graph structures with nodes, edges, and properties. These databases are optimized for complex relationships and connections. Use Cases: Ideal for social networks, recommendation engines, fraud detection, and network analysis. Points about Graph database: Node-Edge Structure Complex Relationships Graph Traversal Pattern Matching High Connectivity

4. 4) Document Database Description : Store data in JSON-like documents. Each document is a set of key-value pairs, and documents can have different structures. Use Cases : Ideal for applications where data structures can vary and evolve, such as content management systems, real-time analytics, and e-commerce platforms. Points about document-oriented databases : JSON Documents Flexible Schema Nested Data Scalable Storage Rich Queries

5. Distribution Model Distribution Model Replication Sharding Master Slave Replication Peer to Peer Replication