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- OLTP (On-line Transaction Processing) 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 System - Online Analytical Processing (Data Warehouse)
- OLTP (On-line Transaction Processing) 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 DatabasesPurpose of data
OLTP: To control and run fundamental business tasksOLAP: To help with planning, problem solving, and decision supportWhat the data
OLTP: Reveals a snapshot of ongoing business processesOLAP: Multi-dimensional views of various kinds of business activitiesInserts and Updates
OLTP: Short and fast inserts and updates initiated by end usersOLAP: Periodic long-running batch jobs refresh the dataQueries
OLTP: Relatively standardized and simple queries Returning relatively few recordsOLAP: Often complex queries involving aggregationsProcessing Speed
OLTP: Typically very fastOLAP: Depends on the amount of data involved; batch data refreshes and complex queries may take many hours; query speed can be improved by creating indexesSpace Requirements
OLTP: Can be relatively small if historical data is archivedOLAP: Larger due to the existence of aggregation structures and history data; requires more indexes than OLTPDatabaseDesign
OLTP: Highly normalized with many tablesOLAP: Typically de-normalized with fewer tables; use of star and/or snowflake schemasBackup and Recovery
OLTP: Backup religiously; operational data is critical to run the business, data loss is likely to entail significant monetary loss and legal liabilityOLAP: Instead of regular backups, some environments may consider simply reloading the OLTP data as a recovery methodsource:
