Skip to main content

Difference between OLTP and DWH/DS/OLAP



                                                                                                                                                                      
Scenario:
Difference between OLTP and DWH/DS/OLAP

Solution:

OLTP
DWH/DSS/OLAP
OLTP maintains only current information.
OLAP contains full history.
It is a normalized structure.
It is a de-normalized structure.
Its volatile system.
Its non-volatile system.
It cannot be used for reporting purpose.
It’s a pure reporting system.
Since it is normalized structure so here it requires multiple joins to fetch the data.
Here it does not require much joins to fetch the data.
It’s not time variant.
Its time variant.
It’s a pure relational model.
It’s a dimensional model.


Comments

Popular posts from this blog

CMN_1650 A duplicate row was attempted to be inserted into a dynamic lookup cache Dynamic lookup error.

Scenario: I have 2 ports going through a dynamic lookup, and then to a router. In the router it is a simple case of inserting new target rows (NewRowLookup=1) or rejecting existing rows (NewRowLookup=0). However, when I run the session I'm getting the error: "CMN_1650 A duplicate row was attempted to be inserted into a dynamic lookup cache Dynamic lookup error. The dynamic lookup cache only supports unique condition keys." I thought that I was bringing through duplicate values so I put a distinct on the SQ. There is also a not null filter on both ports. However, whilst investigating the initial error that is logged for a specific pair of values from the source, there is only 1 set of them (no duplicates). The pair exists on the target so surely should just return from the dynamic lookup newrowlookup=0. Is this some kind of persistent data in the cache that is causing this to think that it is duplicate data? I haven't got the persistent cache or...

SQL Transformation with examples

============================================================================================= SQL Transformation with examples   Use : SQL Transformation is a connected transformation used to process SQL queries in the midstream of a pipeline . We can insert, update, delete and retrieve rows from the database at run time using the SQL transformation. Use SQL transformation in script mode to run DDL (data definition language) statements like creating or dropping the tables. The following SQL statements can be used in the SQL transformation. Data Definition Statements (CREATE, ALTER, DROP, TRUNCATE, RENAME) DATA MANIPULATION statements (INSERT, UPDATE, DELETE, MERGE) DATA Retrieval Statement (SELECT) DATA Control Language Statements (GRANT, REVOKE) Transaction Control Statements (COMMIT, ROLLBACK) Scenario: Let’s say we want to create a temporary table in mapping while workflow is running for some intermediate calculation. We can use SQL transformat...

Load the session statistics such as Session Start & End Time, Success Rows, Failed Rows and Rejected Rows etc. into a database table for audit/log purpose.

                                                                                                                                                                     ...