dbt
Analytics engineering framework that turns SQL into tested data pipelines.
About
dbt is the standard for analytics engineering: data practitioners write SQL models with tests, documentation, and version control, and dbt builds them into trusted warehouse pipelines. Born in 2016 as an open-source CLI (originally Fishtown Analytics), it split into free dbt Core and the paid dbt Cloud SaaS with orchestration, CI, and collaboration features.
In May 2025 dbt Labs announced the dbt Fusion engine, a ground-up Rust rewrite based on technology from its SDF Labs acquisition, delivering up to 30x faster parse times with deep SQL comprehension that catches errors before runtime. Fusion is the future direction for both Core and Cloud, and in November 2025 dbt Labs brought it natively into Microsoft Fabric. dbt Labs now frames itself as the standard for AI-ready structured data, since reliable analytics models are what agents query.
What it can do
- SQL-first data transformation with tests
- Version-controlled, documented pipelines
- dbt Fusion Rust engine with 30x faster parsing
- Native Microsoft Fabric integration
- Mesh and governance for large data teams
Setup
pip install dbt-core with a warehouse adapter, or sign up for dbt Cloud; the Fusion engine works with the new dbt VS Code extension.
Prerequisites
A data warehouse (Snowflake, BigQuery, Postgres, etc.); SQL knowledge.
Use cases
Works with
Trust score — 8/10
Scored 8/10 (verified tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 88; Trending score 80/100 from researcher assessment.
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.