Difference Between ETL and ELT
ETL stands for Extract, Transform & Load, and ELT stands for Extract, Load & Transform, and so in ETL Transforming the data into a common format is done before loading. However, in ELT loading the data to the destination is performed first, and then the transformation is applied based on the destination format. ETL is time consuming compared to ELT, as the ETL is implemented in the staging area and ELT doesn’t have the need for a designated staging process.
What is ETL?
The ETL process involves extracting the data from classified data sources and then to transform and tether the data in a suitable manner, lastly the data is been loaded into data warehouse systems. This Technique is sensible until many dissimilar databases are implicated in the data warehouse landscape. here moving data from one place to another has to happen at anyway so ETL acts as the best practice at these situations to do transformations since the transfer of data is anyhow happening instance here
What is ELT?
It is a slightly different process, The same technique of extract is used here, next the data is loaded into the target systems directly. At the preceding end, the objective systems are accountable for applying the transformations at the loaded data. The major disadvantage here is it usually takes larger time to get the data at the data warehouse and hence with the staging tables an extra step is added in the process, which makes in need for more disk space be available.
Head to Head Comparison Between ETL and ELT (Infographics)
Below are the top 7 differences between ETL vs ELT
Key Differences Between ETL and ELT
There are major key differences between ETL vs ELT are given below:
- ETL is an older concept and been there in the market for more than two decades, ELT relatively new concept and comparatively complex to get implemented.
- In an ETL case, a large number of tools have only one of its kind hardware requirements that are posh. In the case of an ELT Since this falls under Saas hardware cost is not a concern.
- To carry out a lookup, ETL operates row by row pattern to map a fact-value with its dimension key element from a different table. In ELT we can directly map fact-value with dimension key elements.
- In ETL Relational data is prioritized here, whereas ELT Readily supports unstructured data.
Comparison table between ETL vs ELT
Let’s discuss the top 7 difference between ETL vs ELT
| Basis of comparison | ETL | ELT |
| Usage | Implying complex transformations involves ETL | ELT comes into play when huge volumes of data are involved |
| Transformation | Transformations are performed in the staging area | All transformations in target systems |
| Time | Since this process involves loading the data into ETL systems first and then into the respective target system this pulls in a comparatively larger time. | Here since data is directly loaded into the target systems initially and all transformations are carried out at the objective systems. |
| Datalake involvement | No data lake support | Unstructured data can be processed with data lakes here. |
| Maintenance | Maintenance is high here since this process involves two different steps | Maintenance is comparatively low |
| Cost | Higher in the cost factor | Comparatively lower in cost |
| Calculations | Either we need to override an existing column or there is a need to push data at the targeted platform | The calculated column can be easily added |
Conclusion
Every company complied with data warehouse will be using ETL (Extract, Transform, Load) or ELT (Extract, Load, Transform) to push data into the data warehouse which is emerging from different sources. Based on the industry and technical wants, one among the above procedures is widely deployed.
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