// Template · Governance

Database Impact Report

Scans every pipeline and workflow in your project using Apache Hop's built-in RDBMS Impact transform, then writes a structured report to a PostgreSQL table — so you know exactly which pipelines read from or write to a given table before you drop it, rename it, or migrate it.

Uses RDBMS Impact TableOutput

Governance Data Quality DevOps 4 transforms Apache Hop Native only

Download .zip

Apache Hop pipeline
Created May 12, 2026
Hop 2.x+

Pipeline

Hop

RDBMS-Impact

RDBMS_IMPACT

filter-nulls

FilterRows

select-fields

SelectValues

write-report

TableOutput

How it works

This pipeline uses Apache Hop's native RDBMS Impact transform to introspect your entire project — no manual auditing, no grepping through XML files. It finds every database reference across all pipelines and workflows, filters out irrelevant rows, renames the fields for clarity, and writes a clean report to a PostgreSQL table you can query any time.

No Putki plugins required. This template runs entirely on Apache Hop's built-in transforms — RDBMS Impact, FilterRows, SelectValues, and TableOutput. A Putki subscription gives you the scheduler and monitoring, but the pipeline itself needs no extra plugins.

Scan every pipeline and workflow in the project

The RDBMS Impact transform reads all .hpl and .hwf files under ${PROJECT_HOME} and emits one row per database reference it finds — covering TableInput, TableOutput, OdooInput, and any other transform that touches a database connection.

Drop rows with no table reference

Many transforms reference a connection without targeting a specific table. FilterRows discards any row where table is null or empty, keeping the report focused on actual table-level dependencies.

Select and rename fields for the report

SelectValues picks the eight relevant fields and renames them for clarity: filename becomes pipeline, schema becomes schema_name, table becomes table_name. The raw column field is dropped — too granular for a table-level impact report.

Write the report to PostgreSQL

TableOutput truncates and rewrites ${OUTPUT_TABLE} on every run so the report always reflects the current state of the project. Fields are mapped by name automatically. Create the table first using the DDL in rdbms-impact-report.sql.

Output fields

Field	Description
connection	Name of the database connection defined in the Hop project metadata
schema_name	Database schema (e.g. `public`), if specified in the transform
table_name	The target table or view being read from or written to
pipeline	Full path of the `.hpl` or `.hwf` file that contains the reference
file_type	Whether the file is a `Pipeline` or a `Workflow`
item_name	Name of the specific transform or action inside the pipeline
item_type	Transform type — e.g. `TableInput`, `TableOutput`, `OdooInput`
sql_query	The SQL query configured in the transform, when available

What you need

Apache Hop 2.x+

The RDBMS Impact transform is included in Hop 2.x and above. No additional plugins required.

A PostgreSQL database connection

Configure a connection in your Hop project metadata, or update the write-report transform to point to your connection.

The report table created in advance

Run the DDL in rdbms-impact-report.sql (included in the download) to create the table before the first execution.