NoSQL Chapter 1

Get familiar with NoSQL Database

important features of NoSQL
- Schema Flexibility: NoSQL databases do not require a predefined schema
- Horizontal Scalability: scale out by distributing data across multiple servers
- High Availability and Fault Tolerance: built-in replication and sharding features
- Performance: Optimized for specific use cases
- Diverse Data Models: support various data models
- Cost-Effectiveness: the ability to scale out using commodity hardware

Two types of databases
- relational databases
- non-relational databases: often called as NoSQL databases
NoSQL is used to store large quantities of complex and diverse data
MongoDB is one of the most established NoSQL databases
- data aggregation
- ACID
  - atomicity
  - consistency
  - isolation
  - durability
- horizontal scaling
- charts

Relational Database Management
- store structured data
- the data is stored in the form of tables that consists of tows and columns
- the tables can have relationships with other tables
NoSQL Database Management System
- store unstructured and semi-structured data
- allow you to store the data without a schema and also support dynamic schema
- also support dynamic schema

Feature	Relational Database	NoSQL Database
schema	follows a rigid schema	does not impose a rigid schema
data model/storage structure	1. data is stored in tables 2. each record is stored as a row	1. The data is stored in different formats 2. the standard storage structure are documents, graphs, key-values and wide columns
normalization	1. used to remove duplicate data and avoid data anomalies 2. RDB use it to prevents data anomalies	data can be normalized
scaling	hard to scale and are generally scaled vertically	both vertical and horizontal scaling

Key-value
- Image stores
- Key-based filesystems
- Object cache
- Systems designed to scale
Column family
- Web crawler results
- Big data problems that can relax consistency rules
Graph
- Social networks
- Fraud detection
- Relationship-heavy data
Document
- High-variability data
- Document search
- Integration hubs
- Web content management
- Publishing

Dynamic schema: do not have a fixed schema
Horizontal scalability: scale out by adding more nodes to a database cluster
Document-based: Some NoSQL databases, such as MongoDB, use a document-based data model,. Data is stored in a schema-less semi-structured format, such as JOSN or BSON
Key-value-Based: Other NoSQL databases, such as Redis, use a key-value data model. Data is stored as a collection of key-value pairs
Column-bases: Some NoSQL databases, such as Cassandra, use a column-based data model. Data is organized into columns instead of rows
Distributed and high availability: highly available and automatically handle node failures and data replication
Flexibility: support for multiple data types and changing data structures
Performance: optimized for high performance and can handle a high volume of reads and writes

Advantages
- High scalability
- Flexibility
- High availability
- Scalability
- Performance
- Cost-effectiveness
- Agility
Disadvantages
- Lack of standardization
- Lack of ACID co,pliance
- Narrow focus
- Open-source
- Lack of support for complex queries
- Lack of maturity
- Management challenge
- GUI is not available
- Backup
- Large document size

When a huge amount of data needs to be stored and retrieved.
The relationship between the data you store is not that important
The data changes over time and is not structured.
Support of Constraints and Joins is not required at the database level
The data is growing continuously and you need to scale the database regularly to handle the data.