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OLTP

  Here’s a simplified breakdown of the key points from the paragraph: **OLTP in Cloud Computing:** - **Online Transaction Processing (OLTP)**: Used for fast transactions under strict latency requirements. - **Challenges**: Traditional relational databases can't handle the huge data volumes and real-time demands of companies like Google, Amazon, Facebook, etc. - **Solution**: Use **key-value databases** and caching to speed up data access by storing frequently used data in memory. **Memcaching**: - **Memcaching**: Caching system that stores data in memory across many servers, improving access speed. - Uses a **hash table** that stores key-value pairs across multiple servers. - The **LRU (Least Recently Used)** strategy is used to replace old data with new data. **Scalability**: - **Vertical Scaling**: More resources (processors, RAM, etc.) are added to a single system. - **Horizontal Scaling**: More systems (servers) are added, each handling its own data without sharing resources. *...
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NO SQL

**Before Cloud Computing:** - **Hierarchical Model**: Used for strictly parent-child (hierarchical) relationships. - **Network Model**: Handles many-to-many relationships. - **Relational Model**: Most common, proposed by E.F. Codd. Uses tables for data storage. **Relational Databases:** - **SQL (Structured Query Language)**: Language used to manage data in relational databases.   - It has three components:      1. **Data Definition Language (DDL)**: Defines the structure of the data.     2. **Data Manipulation Language (DML)**: Lets you interact with the data (insert, update, delete).     3. **Data Control Language (DCL)**: Manages access to the data (permissions). - **Popular Relational Databases**: Oracle, MySQL, SQLServer, Postgres. **Shift to Cloud Computing:** - With cloud computing came the need to store **unstructured or semi-structured data**, leading to the development of NoSQL databases. - **NoSQL**: Misleading name; it’s not just about ...
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