OLTP vs. OLAP

IT sistemas galime suskirstyti į transactional (OLTP) ir analytical (OLAP).

OLTP - saugo duomenis, vykdo daug on-line transakcijų (INSERT, UPDATE, DELETE).
OLAP - analizuoja, duomenis vaizduoja įvairiais pjūviais.

paimta iš: http://datawarehouse4u.info/OLTP-vs-OLAP.html

Skirtumai tarp OLTP ir OLAP:

	OLTP System Online Transaction Processing (Operational System)	OLAP System Online Analytical Processing (Data Warehouse)
Source of data	Operational data; OLTPs are the original source of the data.	Consolidation data; OLAP data comes from the various OLTP Databases
Purpose of data	To control and run fundamental business tasks	To help with planning, problem solving, and decision support
What the data	Reveals a snapshot of ongoing business processes	Multi-dimensional views of various kinds of business activities
Inserts and Updates	Short and fast inserts and updates initiated by end users	Periodic long-running batch jobs refresh the data
Queries	Relatively standardized and simple queries Returning relatively few records	Often complex queries involving aggregations
Processing Speed	Typically very fast	Depends on the amount of data involved; batch data refreshes and complex queries may take many hours; query speed can be improved by creating indexes
Space Requirements	Can be relatively small if historical data is archived	Larger due to the existence of aggregation structures and history data; requires more indexes than OLTP
Database Design	Highly normalized with many tables	Typically de-normalized with fewer tables; use of star and/or snowflake schemas
Backup and Recovery	Backup religiously; operational data is critical to run the business, data loss is likely to entail significant monetary loss and legal liability	Instead of regular backups, some environments may consider simply reloading the OLTP data as a recovery method

source: www.rainmakerworks.com

OLAP systems really don’t like fragmentation, but OLTP systems do.