OLTP vs OLAP

                                                                 OLAP VS OLTP

Comparison Basis	OLTP (Online Transaction Processing)	OLAP (Online Analytical Processing)
Purpose	Manage day-to-day transaction processing	Support complex queries for data analysis and decision making
Data Type	Current, operational data	Historical, consolidated data
Query Types	Simple, read/write queries	Complex, read-intensive queries
Response Time	Milliseconds to seconds	Seconds to minutes
Data Volume	Smaller, detailed data	Large, aggregated data
Normalization	Highly normalized (to reduce redundancy)	De-normalized (for faster query performance)
Examples	Banking transactions, online purchases	Sales analysis, market research
Users	Clerks, cashiers, front-line staff	Executives, analysts, knowledge workers
Transaction Type	Short and frequent transactions	Long and fewer transactions
Concurrency	High concurrent users	Lower concurrency
Data Integrity	Strict maintenance of data integrity and consistency	Focused on query performance, not real-time data consistency
Schema Design	Entity-Relationship (ER) model	Star or Snowflake schema
Backup and Recovery	Regular and critical	Periodic, based on update cycles
System Requirement	High availability, speed, reliability	High computational power, storage capacity
Typical Operations	Insert, update, delete	Select, aggregate, drill-down
Examples of Systems	CRM systems, ERP systems	Data warehouses, data marts
Data Updates	Real-time	Periodic, batch updates
Focus	Speed and efficiency of transactions	Speed and efficiency of data retrieval