SQL-based data transformation framework
dbt (data build tool) is an open-source SQL transformation framework with 10K+ GitHub stars that lets analytics engineers transform data in their warehouse using select statements. Brings software engineering practices to data — version control, testing, documentation, and CI/CD for SQL. Supports Snowflake, BigQuery, Redshift, Databricks, PostgreSQL, and more. Features Jinja templating, incremental models, snapshots, and a package hub of reusable transformations.
dbt is the standard for data transformation in warehouses using SQL with version control, testing, and modularity.
Write SQL selects, dbt materializes as tables/views/incremental. Jinja adds programming constructs. Auto-generated docs with lineage graphs.
dbt Core is free. dbt Cloud from $100/mo provides managed IDE, scheduling, CI/CD, and semantic layer.
Open-source data transformation framework (Apache-2.0) with managed SaaS cloud tiers. dbt Core is 100% free and open-source for self-hosted CLI and containerized execution with zero licensing fees. dbt Cloud Developer plan is free ($0/mo) for 1 seat with web IDE and job scheduling. dbt Cloud Starter plan costs $100/developer/mo (up to 5-8 seats) with automated CI triggers, Semantic Layer integration, and 15K models/mo. dbt Cloud Enterprise offers custom annual pricing with dbt Mesh multi-project governance, Virtual Private dbt VPC deployment, SAML SSO, RBAC, SOC 2 Type II, and 99.9% uptime SLA.
full pricing breakdown →CLI, dbt Cloud, all major warehouses
Data quality validation framework for Python
Great Expectations is an open-source Python framework for validating, documenting, and profiling data quality. Teams define expectations as expressive unit tests for their data using an intuitive API, then validate datasets against those rules in CI/CD pipelines or production workflows. It connects to pandas, Spark, and SQL sources, generates data documentation automatically, and integrates with orchestrators like Airflow and Prefect for continuous data quality monitoring.
Declarative code-first ELT data integration
Meltano is a declarative, code-first data integration engine with 500+ Singer connectors for building ELT pipelines. It replaces custom API integration code with configuration-driven pipeline definitions that live in version control alongside application code. Integrates with dbt for transformation, supports scheduling and monitoring through a unified CLI, and powers production pipelines at scale.
Verification dates are editorial checks. Routine CMS saves and automatic updatedAt timestamps do not advance them.
dbt (data build tool) is an open-source SQL transformation framework with 10K+ GitHub stars that lets analytics engineers transform data in their warehouse using select statements. Brings software engineering practices to data — version control, testing, documentation, and CI/CD for SQL. Supports Snowflake, BigQuery, Redshift, Databricks, PostgreSQL, and more. Features Jinja templating, incremental models, snapshots, and a package hub of reusable transformations.
dbt offers a free tier alongside paid plans. Open-source data transformation framework (Apache-2.0) with managed SaaS cloud tiers. dbt Core is 100% free and open-source for self-hosted CLI and containerized execution with zero licensing fees. dbt Cloud Developer plan is free ($0/mo) for 1 seat with web IDE and job scheduling. dbt Cloud Starter plan costs $100/developer/mo (up to 5-8 seats) with automated CI triggers, Semantic Layer integration, and 15K models/mo. dbt Cloud Enterprise offers custom annual pricing with dbt Mesh multi-project governance, Virtual Private dbt VPC deployment, SAML SSO, RBAC, SOC 2 Type II, and 99.9% uptime SLA.
Yes — dbt is open source.
Yes — dbt is active. Its listing was last verified on September 6, 2026.
The first editor-selected dbt alternatives are Great Expectations, Meltano.
computed discovery: shared active categories
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