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ETL Pipeline Simulator

Run a real ETL job, one stage at a time. Every stage executes actual SQL against the live database — extract, stage, validate, transform, load, reconcile — and you can pause, step back and replay.

  • 01

    Nothing here is animated theatre. Each stage runs the SQL shown next to it, and the row counts come back from the database.

  • 02

    src_sales arrives dirty. Watch the reject count at the validation stage and the row count difference at load.

  • 03

    Step backwards and the job re-runs deterministically from the top — the only honest way to rewind a data pipeline.

Job control

0 of 6 stages complete

Extracted

0

rows in src_sales

Staged

0

rows landed in stg_sales

Rejected

0

failed a validation rule

Loaded

0

rows published to tgt_sales

Stage 1: Extract

The exact SQL this stage executes

SELECT COUNT(*) AS extracted_rows,
       MIN(sale_date) AS first_date,
       MAX(sale_date) AS last_date
FROM src_sales;

Reject table

Appears once the validation stage has run

Run the job as far as stage 3 and every rejected row shows up here with its reason.

Run something and the rows land here.

Booting SQLite