OLTP (Online Transaction Processing)
Source:
OLTP relies on real-time, transactional data from a single source.
Characteristics:
It manages a large number of small, individual transactions.
Response Time:
Response time is typically in milliseconds.
Performance:
Optimized for fast transaction processing and ensuring data integrity.
Queries:
Queries are very fast, operating on about 5% of the data.
Volume of Data:
Data volume is relatively small, often stored in megabytes (MB) or gigabytes (GB) since historical data is archived.
Operations:
Supports both read and write operations.
Purpose:
Designed for real-time business operations.
Table Structure:
Contains many tables organized in a structured manner.
Examples:
Used for processing payments, managing customer data, and handling order processing.
OLAP (Online Analytical Processing)
Source:
OLAP utilizes historical and aggregated data from multiple sources.
Characteristics:
It handles large volumes of data and supports complex queries.
Response Time:
Response time can range from seconds to hours, depending on the data volume.
Performance:
Optimized for query performance with pre-aggregated data to facilitate faster reporting.
Queries:
Queries are relatively slow due to the large amount of data involved, and they may take hours.
Volume of Data:
Data volume is large, typically stored in terabytes (TB) or petabytes (PB).
Operations:
Primarily supports read operations with rare write operations.
Purpose:
Designed for analyzing business metrics by category and attributes.
Table Structure:
Contains fewer tables, each holding large amounts of data.
Examples:
Used for analyzing trends, predicting customer behavior, and identifying profitability.