OLTP Vs OLAP : Discussion about difference between OLTP vs OLAP system. OLTP is operational system where as OLAP is analytical system.
OLTP stands for Online Transaction Processing ,which typically involves the operational DATA involving the fast query processing, data updation . It basically holds the application data which is necessary to run our business.
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).
Check here for operational vs data warehousing
OLTP Vs OLAP
|Definition||OLTP deals with operational data, which is data involved in the operation of a particular system and it is characterized by a large number of short on-line transactions (INSERT, UPDATE, and DELETE)||An OLAP deals with Historical Data or Archival Data, and it is characterized by relatively low volume of transactions.In addition, the Queries needed for these systems are often very complex and involve aggregations as for OLAP systems the response time is an effectiveness measure.|
|Full Form||Online Transaction Processing||Online Analytical Processing|
|Source of data||Operational data||Consolidation data|
|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|
Here we discussed about the major difference between OLTP vs OLAP.