Difference between ETL and ELT in SQL Server

ETL stands for Extract, Transform and Load. ETL tool is used to extract data from the source RDBMS database and transform extracted data such as applying business logic and  calculation,etc. and  then load data into the target data warehouse. In ETL tool,  transformation of the data performed at the ETL server. It is used for low amount data.

ELT stands for Extract, Load and Transform. ELT tool is also used to extract data from source database and then load data into target database without transformation. In ELT, transformation of data is performed at the target database. In general, in an ELT implementation, all records from the sources are loaded into the data warehouse as part of the extract and loading process. This, linked with the isolation of the transformation phase, means that future requirements can easily be incorporated into the data warehouse architecture.It is used for high amount of data.




Data is moved to ETL server for transformation and then moved back to source database 

Data transformation happened at the target database 


Data redundancy 

ETL model used for on-premises, relational and structured data.

Used in scalable cloud infrastructure which supports structured, unstructured data sources.


Response time 

Response time is dependent on the size of the data.

Response time doesn’t depend on the size of data.


Unstructured Database  

Only support relational database

It also support Unstructured  database