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Commonly confused · Data & Analytics

ETL vs ELT: What's the Difference?

ETL transforms data in a separate processing engine before loading it into the target, so only cleaned data lands in the warehouse. ELT loads raw data into the target first and transforms it there using the scalable compute of a modern cloud warehouse or lakehouse.

ETL (Extract, Transform, Load)

vs

ELT (Extract, Load, Transform)

ETLELT
Transform locationStaging server or ETL engineInside the target warehouse or lakehouse
Raw data kept in targetNoYes
Load speedSlower; waits for transformationFaster ingestion
FlexibilityTransformations defined up frontRe-transform raw data anytime
Best fitOn-premises warehouses, sensitive data that must be cleansed firstCloud warehouses and lakehouses with elastic compute
Example toolsSSIS, Informatica, Azure Data Factory data flowsdbt, Snowflake or BigQuery SQL, Databricks
Remember it

ETL cleans before it moves in; ELT moves in, then cleans.

Exam tip

Expect questions on which pattern suits cloud warehouses (ELT) and which helps remove sensitive data before it reaches the target (ETL). Look at where the T sits in the acronym.

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