Wednesday, June 11, 2014

Olap vs Oltp

Oltp vs olap


Oltp (online transaction processing )is a data modeling approach typically used to facilitate and manage business applications. This kind of data are retrieved in daily, weekly or monthly basis. Usually staff interact with this kind of processing which include (insert ,update ,delete etc) . Short fast query are retrieved from the database. The queries is not very complex and is east to understand.


Olap (online analytical processing) is a data modeling a approach used to analyses large amount of historical data. Historical data are acquired in a large span of time.  Complex queries are needed to retrieve data in olap.


    The following table summarizes the major differences between OLTP and OLAP system design.



    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

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