Azure Data Engineer | Azure Data Engineer Course in Chennai
                     Key Differences 
Between ETL and ELT 
Processes in Azure
Subtitle:
A Guide for Azure Data Engineers
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Introduction to Azure Data Engineering
• Azure provides a scalable cloud ecosystem 
for building modern data pipelines.
• ETL and ELT are two primary approaches 
to ingest, process, and store data.
• Understanding their differences is crucial 
for building efficient solutions.
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What is ETL? (Extract, Transform, Load)
• Data is extracted from source 
systems.
• Transformed in a staging area (on-
prem or cloud).
• Loaded into a destination like 
Azure SQL Database or Synapse 
Analytics.
• Best for complex transformations 
before loading data.
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What is ELT? (Extract, Load, Transform)
• Data is extracted from source systems.
• Loaded directly into Azure Data Lake or 
Synapse Analytics.
• Transformed inside the target system 
using native compute power (e.g., 
T-SQL, Spark).
• Ideal for handling large volumes of raw 
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Tooling in Azure for ETL
• Azure Data Factory (ADF) for 
orchestration.
• Azure Integration Runtime or 
SSIS for transformation.
• Data loaded into Azure 
Synapse or SQL DB post-
transformation.
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Tooling in Azure for ELT
• ADF used primarily for orchestration and 
data movement.
• Data stored in Azure Data Lake or 
Synapse.
• Transformations performed using Synapse 
SQL, Databricks, or Spark pools.
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Key Differences: ETL vs ELT
Feature ETL ELT
Transformation Before loading After loading
Utilizes cloud-native 
Performance Limited by external engine
compute
Use Case Legacy systems Big data & real-time streams
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When to Use ETL or ELT in Azure
• Use ETL when:
– Source data needs cleaning before 
loading
– Regulatory compliance requires 
transformation before storage
• Use ELT when:
–Working with large volumes of semi-
structured or raw data
– Utilizing Synapse or Databricks for 
scalable compute
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Conclusion
• ETL and ELT both play key 
roles in 
Azure data pipelines.
• Choose based on data 
volume, transformation 
complexity, and performance 
needs.
• Azure supports both 
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integrated services.
For More Information About 
Azure DATA Engineering
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   Nilagiri Block, Aditya Enclave,  Ameerpet, 
Hyderabad-16
   Ph. No: +91-998997107
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    [email protected]
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Thank You
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