OLTP ( on-line transaction processing)

OLAP(on-line analytical processing)

OLTP is characterized by a large number of short on-line transactions (INSERT, UPDATE, DELETE). The main emphasis for OLTP systems is put on very fast query processing, maintaining data integrity in multi-access environments and an effectiveness measured by number of transactions per second. In OLTP database there is detailed and current data, and schema used to store transactional databases is the entity model (usually 3NF).

OLAP (On-line Analytical Processing)

is characterized by relatively low volume of transactions. Queries are often very complex and involve aggregations. For OLAP systems a response time is an effectiveness measure. OLAP applications are widely used by Data Mining techniques. In OLAP database there is aggregated, historical data, stored in multi-dimensional schemas (usually star schema).

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

OLTP: Operational data; OLTPs are the original source of the data.

OLAP: Consolidation data; OLAP data comes from the various OLTP Databases

Purpose of data

OLTP: To control and run fundamental business tasks

OLAP: To help with planning, problem solving, and decision support

What the data

OLTP: Reveals a snapshot of ongoing business processes

OLAP: Multi-dimensional views of various kinds of business activities

Inserts and Updates

OLTP: Short and fast inserts and updates initiated by end users

OLAP: Periodic long-running batch jobs refresh the data

Queries

OLTP: Relatively standardized and simple queries Returning relatively few records

OLAP: Often complex queries involving aggregations

Processing Speed

OLTP: Typically very fast

OLAP: 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

OLTP: Can be relatively small if historical data is archived

OLAP: Larger due to the existence of aggregation structures and history data; requires more indexes than OLTP

DatabaseDesign

OLTP: Highly normalized with many tables

OLAP: Typically de-normalized with fewer tables; use of star and/or snowflake schemas

Backup and Recovery

OLTP: Backup religiously; operational data is critical to run the business, data loss is likely to entail significant monetary loss and legal liability

OLAP: Instead of regular backups, some environments may consider simply reloading the OLTP data as a recovery method

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