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SQLMesh
DataOps framework — safe schema evolution, virtual environments, and automated backfills.
0Open Source
ELT & Transform
Overview
SQLMesh is an open-source DataOps framework for transforming data using SQL and Python, with virtual environments, semantic understanding of model changes, and automated backfills to eliminate risky manual migrations.
Key Features
- Virtual environments for safe development without touching production data
- Semantic diff to understand the impact of model changes before deploying
- Automatic incremental backfills for changed models
- Python models alongside SQL models in the same project
- Built-in unit testing with expected row-level assertions
- Drop-in dbt compatibility layer for gradual migrations
Real-World Workflows
Safe production deploys with zero downtime
- 1Develop model changes in a SQLMesh virtual dev environment
- 2Run sqlmesh plan to see which models changed and what backfills are needed
- 3Preview changes in a sandboxed copy without touching production
- 4Apply the plan to promote changes atomically to production
Migrate from dbt incrementally
- 1Point SQLMesh at an existing dbt project directory
- 2Run with dbt compatibility mode — existing models work as-is
- 3Gradually adopt SQLMesh features: virtual envs, semantic diffs
- 4Fully convert models to SQLMesh syntax at your own pace
Getting Started
# Install SQLMesh pip install sqlmesh # Create a new project sqlmesh init ./my_project duckdb cd my_project # Plan and apply changes sqlmesh plan # Run tests sqlmesh test
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