Transformations in Weld

Weld gives you two powerful ways to handle transformations:

  1. Weld Transform — build and schedule models directly in Weld with the SQL editor.
  2. Third-party orchestration — plug in dbt/dbt Core or your warehouse/BI tools while Weld handles ingestion, orchestration, and reverse-ETL.

Weld Transform

Weld’s SQL editor connects directly to your destination (warehouse), so you can write, test, and run SQL models inside Weld.
Perfect if you want one place to build, schedule, and collaborate.

ℹ️ Read the primer on Data Models — drafts, published models, table references, and more.

Key capabilities

  • AI assistant — get SQL help and debugging from Ed
  • Data Lineage — visualize dependencies and impact
  • Version history — track, diff, and roll back changes
  • Scheduling — run models automatically
  • Realtime collaboration — build together with presence and safe concurrency

Guides

Third-party orchestration

Prefer external tools? Weld integrates them into your workflows so you can keep your stack and still get centralized orchestration.

Why choose this path

  • Use familiar tools (dbt, dbt Core, Power BI, Fabric, Looker Studio, Snowflake/BigQuery SQL)
  • Weld handles ingestion and reverse-ETL, plus consistent scheduling and monitoring
  • Reduce manual handoffs; get end-to-end visibility across steps

Integrations

  • dbt Cloud — trigger jobs from Weld; webhook-based orchestration.
    Read setup →

  • dbt Core — run Core externally; Weld powers ingestion + activation.
    Read setup →

  • Other / Webhooks — keep transformations in your warehouse or BI tools.
    Read setup →

✅ Already invested in dbt/BI/SQL? Weld doesn't replace those tools — it connects and orchestrates them within end-to-end workflows.

See the full list here: All Destinations. Common pairings we see:

  • Snowflake — often with dbt/dbt Core; BI via Power BI or SQL-native dashboards.
  • BigQuery — often with dbt/dbt Core; BI via Looker Studio or Power BI.
  • Databricks — often with dbt/dbt Core; BI via Power BI/Fabric.
  • Postgres — lightweight analytics via SQL-based BI or embedded dashboards; orchestration with dbt Core.
  • Amazon S3 (lake/landing) — transformed into your warehouse or queried via warehouse engines; orchestrated alongside dbt/dbt Core.

(That’s just a snapshot — check the Destinations page for everything Weld supports.)

Quick comparison

Use when…Weld TransformThird-party orchestration
You want one place to model & schedule✅—
You already use dbt/BI for transforms—✅
You need centralized lineage/versioning in Weld✅Partial (depends on tool)
You want to keep vendor-native modeling (e.g., Fabric/Power BI)—✅

Next steps

Was this page helpful?