dbt

Founded by Tristan Handy in 2016

Transform, test, and document data in your cloud warehouse using modular SQL code

Pricing model

Free Tier, Paid

Rating

★ Positive

Time to value

> 10 Hours

You can use dbt to transform raw data in your cloud warehouse into clean, structured tables using standard SQL. It lets data teams write modular models, test data quality, and document business logic in a version-controlled environment. You can explore interactive column-level lineage to trace how metrics flow across models, catch logic errors before running queries in production, and automatically propagate column renames. By orchestrating transformations directly inside systems like Snowflake and Databricks, teams reduce compute costs and maintain reliable datasets for analytics and machine learning applications.

What dbt does

Write SQL data transformation modelsInspect interactive column-level DAGsRun automated data validation testsGenerate and view data documentationDefine reusable business metricsPreview refactoring impacts across downstream dependenciesCompile multi-dialect SQL queriesWrite modular data transformations using standard SQL and JinjaTrack interactive data lineage down to the individual column levelRun automated tests to validate data schemas and business rulesAutomatically refactor downstream models when renaming columnsRebuild only modified data models to minimize warehouse compute spendDevelop locally with dedicated extensions for Cursor, VS Code, and WindsurfCentralize business metric definitions with the semantic layer

Pricing breakdown

Pricing model: Free tier, Paid

PlanList price

Developer (per user)Free

Starter (per user)$100 / mo

Frequently asked

Used by

Daniel

Machine Learning Engineer @ Traditum

In their stack

Lorenzo Rosa

Data Analyst @ AWS

In their stack

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