Which architecture will drive your data processing to victory?


ETL and ELT are two essential data integration processes…

Think of them as a manufacturing line in a factory.

ETL - (Extract, Transform, Load)

The Traditional Manufacturing line In this setting…  Raw materials are gathered, processed, and then assembled into a final product.

Data is collected, cleaned, and loaded into a database.  ETL is mainly used to manipulate small amounts of data and it is easy to implement.  ETL is great for those prioritizing data security.

ELT – (Extract, Load, Transform) 

The Modern Manufacturing line  In this case…  All the raw materials are gathered and loaded into a workspace, and then the final product is built.

All the data is loaded into a database and then transformed for analysis.  ELT is used to manage large amounts of data and it requires niche skills to implement.  ELT allows for easy manupilation of data at any stage.

Which road would you take? ETL o ELT?

The choice between ETL and ELT depends on the specific needs of the organization and the type of data being processed.


ETL is typically performed using a batch process and is mainly used for data warehousing and reporting systems where large amounts of historical data are being stored.


ELT is performed in real-time and is mainly used for data analytics and business intelligence systems where up-to-date data is needed for real-time decision making.

The simple answer is… it depends on your needs. 

Which is better?

So, what is your pick?

Which architecture is the best solution for your organization?