[BOOK REVIEW] The Data Warehouse Toolkit by Ralph Kimball/OLAP vs. OLTP
OLAP : Opt for analysis and aggregations for decision-making
Online analytical processing (OLAP) is a system for performing multi-dimensional analysis at high speeds on large volumes of data. -IBM
Examples of OLAP can be financial analysis, sales forcasting, budget planning and so on.
The core of OLAP is the OLAP cube, which is executed on the mechanism of row-by-column and adds layers to data dimensions. The main benefit of OLAP is the consistency of information and calculations. The drawback lies in load performance price for these below mentioning capabilities, especially with large data sets.
Since performance aggregations or precalculated summary tables are often created and managed by the OLAP cube engine, cubes then deliver superior query performance because of the precalculations, indexing strategies, and other optimizations
OLTP: Opt for execution, transaction
Online transactional processing (OLTP) enables the real-time execution of large numbers of database transactions by large numbers of people, typically over the Internet. — IBM
Examples of OLTP system can be everyday transactions, ATMs, online shopping, hotel or flight reservation and so on.
For OLTP transactions and responses, every millisecond counts.
OLTP systems use a relational database that can do the following:
- Process a large number of relatively simple transactions — usually insertions, updates and deletions to data.
- Enable multi-user access to the same data, while ensuring data integrity.
- Support very rapid processing, with response times measured in milliseconds.
- Provide indexed data sets for rapid searching, retrieval and querying.
- Be available 24/7/365, with constant incremental backups.
