What are OLTP and OLAP?
They both are databases that get designed to serve different purposes – OLTP denotes Online Transaction Processing and OLAP denotes Online Analysis Processing.
What’s common for OLTP and OLAP is that they both are used for data warehousing, and a significant difference in the OLTP vs OLAP comparison is that OLTP can also be used outside of data warehousing whereas OLAP will be used only for data warehousing.
OLTP vs OLAP – Key differences
The key point of differentiation in OLTP vs OLAP is the OLTP becomes the online transaction system while OLAP gets recognized as the online data retrieval as well as analysis system
- OLTP will be leveraged for insert, update as well as delete operations – this sets the rationale for using OLTP behind application in terms of enabling regular business transactions
- OLAP powered databases serve the purpose of enabling read operation and facilitating analysis, mining as well as reporting on large datasets
- A key point to be taken note of is that the database used for storing all Facts and Dimensions point to the OLTP. After this, when data is moved for creating a cube, it gets stored in OLAP database
OLTP vs OLAP – Salient Features of Comparison
- As we take a look at OLTP vs OLAP differences in terms of querying, OLAP queries turn out to be more complex as when compared to that of OLTP
- Another significant element of OLTP vs OLAP is the processing, wherein OLAP’s transactions consumer more time when compared to OLTP
- Data integrity is yet another critical feature of the OLTP vs OLAP comparison. OLTP databases are frequently updated, wherein data integrity constraints should be maintained carefully. On the other hand, OLAP is not modified very frequently (incrementally over some time as a big transaction), wherein data integrity is usually not affected.
The figure below highlights major differences in the OLTP vs OLAP topic when a comparison is made between OLTP and OLAP systems.
Digging deeper into OLTP vs OLAP differences
- Cube is the core of OLAP system, and this is but three-dimensional spreadsheet whereas it is the 2D tables where OLTP data gets stored
- A cube comprises Numeric Facts known as measures and it is the dimension data that is used for their categorization
- For any cube, metadata is Snowflake schema or star schema or Fact Constellation with respect to relational (OLTP) database
- In OLTP, CRUD operation can be performed whereas there are more operations that can be performed on cube as that of slicing, dicing and pivoting among others