Ritu Palod

Ritu Palod

I am an Information Systems masters with prior 6 years of extensive experience creating Business Intelligence solutions.

ETL vs ELT: 2 similar yet different approaches

1 minute read

Extraction -> Transform -> and Load

ETL image

ETL is the extraction of data from different form of data sources and then transforming it to a data warehouse specific format. It is then loaded into the data warehouse for further processing of data for analytical purposes. It tends to write data from a source to a target with the help of integration tools like SSIS, Talend, Informatica, etc.

A transform function requires business logic to convert a source data to a business beneficent data form, which is then passed on to the load function.

A load function is primarily responsible to load this transformed data into the warehouse to produce analytical outputs thereby completing the integration process.

While ETL requires to transform (put business logic to convert data) the extracted data and then load. It requires comparatively more time to process data as the data is in a pipeline.

Whereas, when we follow the ELT.

Extraction –> Load -> and Transform

ELT image

ELT directly transforms data from source to target.Thereby leveraging the target data system to do the transformation. This is primarily helpful when the target system is a powerful data engine, for example, Hadoop, NoSQL etc.

ETL vs ELT

  1. ELT is a more reliable form of data integration if there is a powerful target data engine. Otherwise, it’s ETL for rest of the cases.

  2. ETL takes up more memory space as it transforms the whole data between source and target which is not the case in ELT.

  3. Although it takes time to write the business logic for the transformation of data in ETL, the end result is, it is faster as the target system gets a simplified data format to which further analytics can be performed helpful to business analysts.

Whereas, in ELT although the data reaches faster to target system, it bears the load of then computing the necessary business transformation and yields, slower outputs to the analysts.

  1. ETL is compile-time whereas ELT is a run-time process.

  2. ELT is more flexible than ETL as, the transformation logic can be changed at run-time, whereas that is not the case in ETL.

ELT and ETL are excellent tools to use. However, knowing which to use and when is the ultimate game changer.

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