> For the complete documentation index, see [llms.txt](https://gchandra.gitbook.io/data-warehousing/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://gchandra.gitbook.io/data-warehousing/fundamentals/8-steps-to-design-a-data-warehouse/choosing-etl-elt-solution.md).

# Choosing ETL / ELT Solution

### ETL

* Extract
* Transform
* Load

ETL plays a vital part in moving data across.

Many ways ETL can be implemented.

### Popular ones

GUI Tools such as SSIS, Pentaho, Talent

Scripting Tools such as Bash, Python

### ELT

* Extract
* Load
* Transform

In big data platforms such as Hadoop, and Spark, you can load a JSON, or CSV file and start using them as is. This technology can even parse compressed .gz / .bz2 files

Extensively used when dealing with Semi-Structured databases.

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