Difference Between Operational Database System and Dataware Houses in Tabular Form
| Sno. | Operational Database System (OLTP) | Dataware Houses |
| 1. | This involves day to day processing.This contains current data. | This involves processing of information.This contains historical data. |
| 2. | This provides detailed and flat relational view of data. | This provides sum marized and multi-dimensinal view of data. |
| 3. | This is based on star schema, snow flake schema and Fact constellation schema. | This is based on Entity relationship model. |
| 4. | Data is dynamic. | Data is largely static. |
| 5. | Repetitive processing. | Adhoc, unstructured and heuristic processing. |
| 6. | High level of transaction throughput. | Medium to low level of transaction throughput. |
| 7. | Number of rewards accessed are in tens. | The number of rewards accessed are in millions. |
| 8. | lt supports day-to-day decisions. | lt supports strategic decisions. |
| 9. | lt serves large number of clerical/operational users. | lt serves relatively low number of managerial users. |
| 10. | OLAP systems are used by knowledge workers such as executive, manager and anlayst. | OLTP system are used by clerk, DBA or database professionals. |
| 11. | Data within operational systems are generally updated regularly. | Data within a data warehouse is non-volatile, meaning when new data is added old data is not erased so rarely updates. |
| 12. | Complex data structures. | Multi dimensional data structures. |
| 13. | lt is used for Online Transactional Processing (OLTP) | lt is used for Online Analytical Processing (OLAP). |
| 14. | Operational systems represent current transactions. | Data warehousing systems reads the historical data. |
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