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A pipeline (also called a job) connects a source to a destination and defines how data flows between them. This guide walks you through creating one from scratch.
Make sure you’ve completed Create a Connection before this step.

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Creating a pipeline

  1. Select Data → Jobs in the sidebar.
  2. Click New Job (page title New job). Give the Job a name (for example postgres-to-snowflake-orders).
  3. Complete the wizard: Source → Destination → Tables → Field Mapping → Configure.
  4. On Source, choose the source connection — after catalog scan / profiling, Zwiron lists available tables and schemas.
  5. On Destination, choose the destination connection. Destination schema defaults from the source connection name (for example prod_postgres); override on Configure if needed.
  6. On Tables, select tables (or use manual entry when offered).
  7. On Configure, set execution mode (Hosted or Agent), sync mode, destination write mode, schedule, and optional advanced Job Type (ETL / Reverse ETL).
  8. Click Create Job.
  9. On the Job detail page, click Rerun to start immediately, or wait for the schedule.
Zwiron creates destination tables automatically when they do not exist, mapping source column names and types.

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Sync modes

Best for: Small tables, lookup tables, or when you always want a clean copy.On every run, Zwiron reads the entire source table and replaces the destination table. This is the simplest mode — no special source configuration required.
  • Works with any source
  • No cursor or primary key required
  • Destination table is truncated and reloaded each run

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Transforms

Before saving, you can apply transforms to filter or reshape data in transit:
  • Drop column — exclude columns from reaching the destination (common for PII)
  • Rename column — write a column under a different name at the destination
  • Type cast — change the Arrow type of a column (e.g. int32 → utf8)
  • Hash column — replace values with SHA-256 hashes to pseudonymize PII
  • Row filter — only sync rows that match a condition
See Transforms for the full reference.

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Scheduling

CDC jobs run continuously — they don’t use a schedule. Once started, they stream changes until you pause or stop the job.

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Monitoring your pipeline

Click into the job to see:
  • Status — Running, Completed, Failed, Cancelled
  • Progress — tables synced, rows transferred, bytes moved
  • Last run — duration, row count, any errors
  • Next run — when the job is scheduled to run again
  • Logs — full run-level event log for debugging
See Monitoring for the full reference.

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What’s next?

CDC deep dive

How Change Data Capture works and how to enable it

Transforms

Filter, rename, and type cast columns

Scheduling

Cron schedules and trigger options

All connectors

See every supported source and destination
Last modified on October 10, 2026