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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. Click Jobs in the sidebar
  2. Click New Job and give the job a name (e.g. postgres-to-snowflake-orders)
  3. Select your source connection — Zwiron discovers all available tables and schemas automatically
  4. Select your destination connection
  5. Select the tables you want to sync (select individual tables, entire schemas, or search by name) — the destination schema is auto-generated from the source connection name (e.g. prod_postgres). You can override it in the configure step if needed.
  6. Choose an execution mode — Hosted if both ends are cloud-reachable, or Agent to run inside your network
  7. Choose a sync mode (see below)
  8. Optionally configure transforms to filter or reshape data in transit
  9. Set a schedule for when the job should run
  10. Click Save & Run to start immediately, or Save to start on the next scheduled run
Zwiron creates destination tables automatically if they don’t exist, matching the 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 July 13, 2026