SQLMesh/sqlmesh

SQLMesh/sqlmesh has 3,348 GitHub stars and 484 forks. GitHot measured 0 stars in 24 hours and +2 in 7 days. Last checked 2026-11-12 11:44 UTC. Last push 2026-11-02.

这些数字如何统计

Scalable and efficient data transformation framework - backwards compatible with dbt.

3,348 星标 484 forks

可以做什么

See a full diagram of how Virtual Data Environments work
Watch this video to learn more
Create isolated development environments without data warehouse costs
Plan / Apply workflow like Terraform to understand potential impact of changes

实测星标增长

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README.md

原文

SQLMesh logo

SQLMesh is a project of the Linux Foundation.

SQLMesh is a next-generation data transformation framework designed to ship data quickly, efficiently, and without error. Data teams can run and deploy data transformations written in SQL or Python with visibility and control at any size.

It is more than just a dbt alternative.

Architecture Diagram

Core Features

Get instant SQL impact and context of your changes, both in the CLI and in the SQLMesh VSCode Extension

Virtual Data Environments

See a full diagram of how Virtual Data Environments work
Watch this video to learn more

Create isolated development environments without data warehouse costs
Plan / Apply workflow like Terraform to understand potential impact of changes
Easy to use CI/CD bot for true blue-green deployments

Efficiency and Testing

Running this command will generate a unit test file in the tests/ folder: test_stg_payments.yaml

Runs a live query to generate the expected output of the model

sqlmesh create_test tcloud_demo.stg_payments --query tcloud_demo.seed_raw_payments "select * from tcloud_demo.seed_raw_payments limit 5"

# run the unit test
sqlmesh test

MODEL (
  name tcloud_demo.stg_payments,
  cron '@daily',
  grain payment_id,
  audits (UNIQUE_VALUES(columns = (
      payment_id
  )), NOT_NULL(columns = (
      payment_id
  )))
);

SELECT
    id AS payment_id,
    order_id,
    payment_method,
    amount / 100 AS amount, /* `amount` is currently stored in cents, so we convert it to dollars */
    'new_column' AS new_column, /* non-breaking change example  */
FROM tcloud_demo.seed_raw_payments

test_stg_payments:
model: tcloud_demo.stg_payments
inputs:
    tcloud_demo.seed_raw_payments:
      - id: 66
        order_id: 58
        payment_method: coupon
        amount: 1800
      - id: 27
        order_id: 24
        payment_method: coupon
        amount: 2600
      - id: 30
        order_id: 25
        payment_method: coupon
        amount: 1600
      - id: 109
        order_id: 95
        payment_method: coupon
        amount: 2400
      - id: 3
        order_id: 3
        payment_method: coupon
        amount: 100
outputs:
    query:
      - payment_id: 66
        order_id: 58
        payment_method: coupon
        amount: 18.0
        new_column: new_column
      - payment_id: 27
        order_id: 24
        payment_method: coupon
        amount: 26.0
        new_column: new_column
      - payment_id: 30
        order_id: 25
        payment_method: coupon
        amount: 16.0
        new_column: new_column
      - payment_id: 109
        order_id: 95
        payment_method: coupon
        amount: 24.0
        new_column: new_column
      - payment_id: 3
        order_id: 3
        payment_method: coupon
        amount: 1.0
        new_column: new_column

Never build a table more than once
Track what data’s been modified and run only the necessary transformations for incremental models
Run unit tests for free and configure automated audits
Run table diffs between prod and dev based on tables/views impacted by a change

Level Up Your SQL

Write SQL in any dialect and SQLMesh will transpile it to your target SQL dialect on the fly before sending it to the warehouse. Transpile Example

Debug transformation errors before you run them in your warehouse in 10+ different SQL dialects
Definitions using simply SQL (no need for redundant and confusing Jinja + YAML)
See impact of changes before you run them in your warehouse with column-level lineage

For more information, check out the documentation.

Getting Started

Install SQLMesh through pypi by running:

mkdir sqlmesh-example
cd sqlmesh-example
python -m venv .venv
source .venv/bin/activate
pip install 'sqlmesh[lsp]' # install the sqlmesh package with extensions to work with VSCode
source .venv/bin/activate # reactivate the venv to ensure you're using the right installation
sqlmesh init # follow the prompts to get started (choose DuckDB)

Note: You may need to run python3 or pip3 instead of python or pip, depending on your python installation.

Windows Installation

mkdir sqlmesh-example
cd sqlmesh-example
python -m venv .venv
.\.venv\Scripts\Activate.ps1
pip install 'sqlmesh[lsp]' # install the sqlmesh package with extensions to work with VSCode
.\.venv\Scripts\Activate.ps1 # reactivate the venv to ensure you're using the right installation
sqlmesh init # follow the prompts to get started (choose DuckDB)

Follow the quickstart guide to learn how to use SQLMesh. You already have a head start!

Follow the crash course to learn the core movesets and use the easy to reference cheat sheet.

Follow this example to learn how to use SQLMesh in a full walkthrough.

Join Our Community

Connect with us in the following ways:

Join the Tobiko Slack Community to ask questions, or just to say hi!
File an issue on our GitHub
Send us an email at [email protected] with your questions or feedback
Read our blog

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines on how to contribute, including our DCO sign-off requirement.

Please review our Code of Conduct and Governance documents.

Read more on how to set up your development environment.

License

This project is licensed under the Apache License 2.0. Documentation is licensed under CC-BY-4.0.

SQLMesh/sqlmesh

可以做什么

实测星标增长

README.md

Core Features

Getting Started

Join Our Community

Contributing

License

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