dbt

SQL-based transformation layer for the 'T' in ELT

Overview

dbt is not an extraction tool: it handles the transformation step of ELT by compiling SQL (and Python) models into queries that run inside the warehouse, with version control, testing, documentation and lineage. It is included here because most modern ELT stacks pair an ingestion tool with dbt. dbt Labs merged with Fivetran in an all-stock deal completed on 1 June 2026, and the dbt Fusion engine runtime was open-sourced as dbt Core v2.0 (alpha) under the Apache 2.0 licence[3].

The managed product has four tiers. Developer is free for one seat with 3,000 models built per month and includes the browser IDE, job scheduling and CI checks but no API access; Starter costs US$100 per user per month for up to five seats, 15,000 models built and 5,000 semantic-layer metric queries; Enterprise and Enterprise+ are custom-priced with 100,000 models built and 30 or unlimited projects[16]. A 14-day trial includes all features[16]. The main limitation for buyers comparing ETL tools is scope: dbt needs a separate ingestion product and a warehouse, and per-seat pricing grows with team size.

What dbt does

  • SQL and Python models compiled to warehouse queries
  • Built-in tests, documentation and lineage
  • Browser IDE and job scheduler
  • Semantic layer metrics
  • CI checks on pull requests
  • Open-source dbt Core

dbt pricing

Developer: free, 1 seat, 3,000 models built/month. Starter: US$100 per user/month, up to 5 seats, 15,000 models built, 5,000 metric queries. Enterprise and Enterprise+: custom, 100,000 models built, 30 or unlimited projects. 14-day trial.

dbt strengths and limitations

Strengths

  • De facto standard for in-warehouse transformation
  • Free tier and open-source core
  • Testing and lineage built in
  • Published per-seat price

Limitations

  • No extraction or loading
  • Per-seat cost scales with team size
  • API access not on free plan
  • Requires SQL skills

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