OLTP v/s OLAPMarch 5, 2009 by Deepanshu Mehta We can divide IT systems into transactional (OLTP) and analytical (OLAP). In general we can assume that OLTP systems provide source data to data warehouses, whereas OLAP systems help to analyze it. OLTP (On-line Transaction Processing) is characterized by a large number of short online 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. 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. The following table summarizes the major differences between OLTP and OLAP system design. OLTP System OLAP System Online Transaction Processing Online Analytical Processing (Operational System) (Data Warehouse) Operational data; OLTPs are the Consolidation data; OLAP data comes Source of data original source of the data. from the various OLTP Databases To control and run fundamental To help with planning, problem Purpose of data business tasks solving, and decision support Reveals a snapshot of ongoing Multi-dimensional views of various What the data business processes kinds of business activities Inserts and Short and fast inserts and updates Periodic long-running batch jobs Updates initiated by end users refresh the data Relatively standardized and simple Often complex queries involving Queries queries Returning relatively few aggregations records Depends on the amount of data involved; batch data refreshes and Processing Typically very fast complex queries may take many Speed hours; query speed can be improved by creating indexes Larger due to the existence of Space Can be relatively small if historical aggregation structures and history Requirements data is archived data; requires more indexes than OLTP Database Highly normalized with many Typically de-normalized with fewer

Design

tables

tables; use of star and/or snowflake schemas

Backup religiously; operational Instead of regular backups, some data is critical to run the business, Backup and environments may consider simply data loss is likely to entail Recovery reloading the OLTP data as a recovery significant monetary loss and legal method liability