2013 m. vasario 3 d., sekmadienis

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.

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