MongoDB Database

MongoDB is a popular open-source NoSQL database that stores data in flexible, JSON-like documents instead of the tables and rows found in traditional relational databases. This document-oriented model allows for a dynamic and schema-less architecture, meaning fields can vary from document to document, which provides significant flexibility for developers and is well-suited for handling unstructured or semi-structured data. Designed for high performance and horizontal scalability, MongoDB is a prominent choice for modern applications, particularly in big data, content management, and real-time services where agility and the ability to handle large, diverse datasets are critical.

1. Introduction to NoSQL and Document Databases
   1. Understanding Database Models
      1. Characteristics of Relational Databases (SQL)
         1. Tables, Rows, and Columns
         2. Structured Query Language (SQL)
         3. Fixed Schema Requirements
         4. ACID Properties
            1. Atomicity
            2. Consistency
            3. Isolation
            4. Durability
         5. Normalization Principles
         6. Referential Integrity
      2. Characteristics of Non-Relational Databases (NoSQL)
         1. Flexible Schema Design
         2. Horizontal Scalability
         3. BASE Properties
            1. Basically Available
            2. Soft State
            3. Eventual Consistency
         4. Use Cases for NoSQL
         5. CAP Theorem Implications
         6. Performance Characteristics
   2. Types of NoSQL Databases
      1. Key-Value Stores
         1. Data Structure and Storage Model
         2. Use Cases and Applications
         3. Performance Characteristics
         4. Examples and Implementations
      2. Document Stores
         1. Document-Oriented Data Model
         2. JSON and BSON Documents
         3. Schema Flexibility
         4. Query Capabilities
         5. Examples and Implementations
      3. Column-Family Stores
         1. Column-Oriented Data Model
         2. Wide Column Architecture
         3. Use Cases and Applications
         4. Examples and Implementations
      4. Graph Databases
         1. Nodes, Edges, and Properties
         2. Graph Traversal Algorithms
         3. Use Cases and Applications
         4. Examples and Implementations
   3. Introduction to MongoDB
      1. Core Philosophy and Design Principles
         1. Document-Oriented Storage
         2. Flexibility and Scalability
         3. Developer-Focused Design
         4. Open Source Foundation
      2. Key Features
         1. Flexible Schema
            1. Schema-Less Collections
            2. Evolving Data Models
            3. Schema Validation Options
         2. High Performance
            1. In-Memory Storage Engine
            2. Efficient Indexing
            3. Query Optimization
         3. High Availability
            1. Replica Sets
            2. Automatic Failover
            3. Data Redundancy
         4. Scalability
            1. Horizontal Sharding
            2. Vertical Scaling Options
            3. Load Distribution
      3. Common Use Cases
         1. Content Management Systems
         2. Real-Time Analytics
         3. Internet of Things (IoT)
         4. Catalogs and Inventory Management
         5. Mobile Applications
         6. Social Media Platforms
      4. MongoDB Ecosystem Overview
         1. Community vs Enterprise Editions
         2. MongoDB Atlas Cloud Service
         3. Third-Party Tools and Integrations
   4. The JSON and BSON Data Formats
      1. JavaScript Object Notation (JSON)
         1. Syntax and Structure
         2. Data Types Supported
            1. String
            2. Number
            3. Boolean
            4. Array
            5. Object
            6. Null
         3. Human-Readability
         4. Limitations and Constraints
      2. Binary JSON (BSON)
         1. Structure and Encoding
         2. BSON Data Types
            1. String
            2. Integer (32-bit and 64-bit)
            3. Double
            4. Boolean
            5. Date
            6. ObjectId
            7. Array
            8. Embedded Document
            9. Binary Data
            10. Regular Expression
            11. JavaScript Code
            12. Timestamp
            13. Decimal128
         3. Advantages of BSON over JSON
            1. Richer Data Types
            2. Efficient Storage and Traversal
            3. Support for Binary Data
            4. Faster Parsing
         4. BSON Size Limitations
         5. Conversion Between JSON and BSON