ETL/ELT is used for migration of data from one database to another in order to form data marts and data warehouses and also to convert databases from one format to another.
ETL Architecture
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In order to control the databases, extract, transform, load (ETL) classifies to three separate states combined into a ETL tool. First, the extract state reads data from a specified source database and extracts a subset of source data. Next, the transform state it adds the transformation logic (like look-up, union, combinations with other data) on top of the selected source data in order to convert it to the desired state. Finally, the load state is used to write the resulting data (either all of the subset or just the changes) to a target database.
In Short, - Extract -- the action of reading data from a database.
- Transform -- the action of transforming the extracted data from its previous form into the resultant form.
- Load -- the action of writing the data into the target database.
Examples: Some of leading ETL tools presently in the market: - IBM WebSphere Information Integration (Ascential DataStage)
- Ab Initio
- Informatica
- Talend
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ELT Architecture
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ELT also has the same 3states similar to the ETL but the only difference is the order. ELT (Extract, Load and Transform) which is driven by RDBMS which transforms and migrates data, often by generating SQL statements and procedures and moving data between tables.
In Short,
- Extract -- the action of reading data from a database.
- Load & Transform -- the action of transforming and writing into the target database using the target database power.
Examples: Some of leading ETL tools presently in the market: - Oracle data integrator/Sunopsis
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Difference between ELT & ETL
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