0.Extra.md

Extras

Q. Difference between relational, object-oriented, nosql, hierarchical DB

Feature	Relational Database	Object-Oriented Database	NoSQL Database	Hierarchical Database
Data Model	Tables with rows and columns	Objects, classes, inheritance	Key-Value, Document, Column, Graph	Tree structure with parent-child relationships
Schema	Fixed schema	Schema follows object classes	Flexible schema	Rigid schema
Query Language	SQL	Object Query Language (OQL)	Varies (e.g., MongoDB uses MQL)	None (typically uses path queries)
Data Storage	Rows in tables	Objects	Varies (e.g., JSON, BSON, etc.)	Hierarchical structure with linked nodes
Scalability	Vertical scaling	Vertical scaling	Horizontal scaling	Vertical scaling
ACID Compliance	Strong ACID properties	Supports ACID	Varies (often BASE over ACID)	Strong ACID properties
Relationships	Foreign keys, joins	Direct references via objects	Denormalized, typically no joins	Parent-child relationships
Examples	MySQL, PostgreSQL, Oracle	db4o, ObjectDB	MongoDB, Cassandra, DynamoDB	IBM Information Management System (IMS)
Use Cases	Traditional applications, ERP, CRM	CAD, telecommunications, complex data models	Big data, real-time web apps, flexible data models	Legacy systems, hierarchical data like XML or LDAP
Advantages	Maturity, standardization, strong consistency	Aligns with OOP, seamless integration with object-oriented languages	Flexibility, scalability, performance	Simple model, fast data retrieval for specific use cases
Disadvantages	Rigid schema, scaling limitations	Complexity, less maturity than RDBMS	Potential consistency issues, varied tooling	Rigid structure, inflexible for complex queries

Difference between Relational and NoSQL

Relational	NoSQL
Has strict schema/structure	Schemaless
Row-column format	JSON format
Predictable Data	Difficult to predict data
Performance issues while reading with large set of data and relationships	Better at reading from large data set as it supports complex nested structure.
MySQL, Postgres, SQL Server	MongoDB, DynamoDB, CouchDB

Difference between MongoClient.connect(url) vs mongoose.connect(url)

Feature/Aspect	MongoClient.connect(url)	mongoose.connect(url)
Library	mongodb Node.js driver	Mongoose (ODM library for MongoDB and Node.js)
Abstraction Level	Low (direct interface to MongoDB)	High (provides schema-based data modeling)
Typical Use Case	Direct access and control over MongoDB	Schema-based data modeling, handling relationships, validation
Pros	- Full control over MongoDB operations	- Simplifies working with MongoDB using schemas and models
	- Suitable for fine-grained control	- Built-in data validation, middleware support
Cons	- Requires more boilerplate code	- Adds abstraction overhead
	- Less convenient for complex data models	- Might be overkill for basic database operations