There are 4 main types of NoSQL databases: key-value stores, column family stores, document databases, and graph databases. Key-value stores store unique keys mapped to values, column family stores organize data into columns and column families, document databases store documents as values identified by unique keys, and graph databases represent data as nodes connected by edges to model relationships. Each type has different strengths for certain types of data based on structure, relationships, and querying needs.

1. Types of NoSQL Databases:
Key-value
stores
Column
Family stores
Document
Databases
Graph
Databases
4 Types of NoSQL Databases are

2. Key Value (tuple) Stores
•Implements Hash Table methodology
•Unique Keys & values with index pointers
•Simple and Easy to implement
•Pros: performance, scalability, flexibility
•Cons: No Schema
•Best with: Less complex huge data sets
Keys Values
Id 1 Name 1
Id 2 Name 2
Id 3 Name 3

3. Column Family Stores
• Stores data using unique keys & multiple columns
•Main Concept: creating Columns – Column Families – Super
Columns
•Column Family - collection of columns with key-value pair
•Super Column - collection of column families but not other
super columns
•Best with: Complex data sets
•Pros: Scalability & Performance
•Cons: Flexibility
Name (key)
Value1
FirstName
Value2
MidlleName
Value3
LastName

4. Document Databases
• Each document can be identified with unique keys
• Every document act as a value (JSON documents)
• Also called Semi-Structured data
• Has inter-related values associated with keys
• Best with: file/document related complex data
• Pros: flexibility, scalability, performance
• Cons: Querying
Keys Document
Id 1 Document1 with key-value collection
Id 2 Document2 with key-value collection
Id 3 Document3 with key-value collection

5. Graph Databases
• Implements Graph Theory in a flexible graph model
• Data can be represented with N - number of inter-related
relations as edges between nodes or documents
• No rows & columns
• Data specific model needs RESTful interfaces
• Best with: Data with complex but definitive relations
• Pros: Flexibility
• Cons: Clustering, performance, complexity