Data Analysis & Investment Research · Public

sqlmesh

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

Best fitUsers who want source-backed project understanding before installing it.

Check whether this project matches your task before installing it.

What it can doskill, recipe, host_instruction, eval, preflight

Review the portable capability path.

Before continuingVerify in a sandbox

Do not treat a preview pack as a proven local install.

GitHub snapshot3.1k stars

403 forks · 141 contributors

Doramagic.ai Last verification date: 2026-06-19 Verification method: source evidence, semantic profile, public page gate, and static build acceptance.

Official first step Read manual preview Source repository

Publication status · 2026-06-19

What is sqlmesh?

Scalable and efficient data transformation framework - backwards compatible with dbt.
Best fit: Users who want source-backed project understanding before installing it.
Not for: Not for users who want to skip sandbox verification or cannot accept configuration, permission, or maintenance overhead.
Capability added to an AI workflow: skill, recipe, host_instruction, eval, preflight
First safe verification step: Verify the smallest path in an isolated environment and keep a rollback path.
Verification state: source, Quick Start, and sandbox install checks are recorded as passed.
Top risk: May increase setup, validation, or first-run risk for the user.
Evidence base: https://github.com/SQLMesh/sqlmesh, https://github.com/SQLMesh/sqlmesh#readme, Human Manual, Pitfall Log

Quick decision

Use this section to decide whether the project is worth a deeper read.

Best forUsers who want source-backed project understanding before installing it.

Match the project to your task before installing it.

Capabilityskill, recipe, host_instruction, eval, preflight

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

RepositorySQLMesh/sqlmesh

3.1k stars · 403 forks

What it can do

Translate the upstream project into concrete capabilities the user can judge before installing.

SQLMesh Overview and Core Architecture

Related topics: Database Engine Adapters and External Integrations, State Management, Migrations, and CI/CD

Source: https://github.com/SQLMesh/sqlmesh / Human Manual

Database Engine Adapters and External Integrations

Related topics: SQLMesh Overview and Core Architecture, State Management, Migrations, and CI/CD

Source: https://github.com/SQLMesh/sqlmesh / Human Manual

LSP, VSCode Extension, and Web UI

Related topics: SQLMesh Overview and Core Architecture

Source: https://github.com/SQLMesh/sqlmesh / Human Manual

State Management, Migrations, and CI/CD

Related topics: SQLMesh Overview and Core Architecture, Database Engine Adapters and External Integrations

Source: https://github.com/SQLMesh/sqlmesh / Human Manual

Doramagic Pitfall Log

Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.

Source: Doramagic discovery, validation, and Project Pack records

Sources: https://github.com/SQLMesh/sqlmesh, Human Manual, Project Pack evidence, and downstream validation signals.

Community Discussion Evidence

Project-level external discussion stays visible on the detail page, not only inside the manual.

Stars3.1k stars

Forks403 forks

Contributors141 contributors

Licenseunknown

Community Discussion Evidence

12 source-linked items

Review these external discussions before using sqlmesh with real data or production workflows. They are review inputs, not standalone proof that the project is production-ready.

01
Databricks runs fail to execute on 0.235.4 with thrift error
github / github_issue
02
Model is missing but sqlmesh plan/run is successful
github / github_issue
03
Table reference with the same name as a preceding CTE are missed from de
github / github_issue
04
Upgrade to sqlglot 30.9.0 to support external dialect plugins
github / github_issue
05
`databricks_connect_cluster_id` is ignored — Databricks Connect always f
github / github_issue
06
Feature request: Blueprinted names for the columns with a Python data fr
github / github_issue
07
Add scoped snapshot cleanup to `invalidate` command
github / github_issue
08
Failed lookback interval runs create data holes
github / github_issue
09
v0.235.4
github / github_release
10
v0.235.3
github / github_release
11
v0.235.2
github / github_release
12
v0.235.1
github / github_release

How to start

Only source-backed commands are shown here. Verify them in an isolated environment first.

Try the prompt first

Test the workflow without installing the upstream project.

preview

Read the Human Manual

Understand inputs, outputs, limits, and failure modes.

manual

Take context to your AI host

Use the compiled assets in your preferred AI environment.

context

Run sandbox verification

Confirm install commands and rollback before using a primary environment.

verify

pip install sqlmesh

Official start command · https://github.com/SQLMesh/sqlmesh#readme · verified: yes

Human Manual

The English page must expose the real manual, not a short placeholder.

8+ sections · Human Manual

sqlmesh Manual

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

Open the full manual

https://github.com/SQLMesh/sqlmesh Project Manual
Table of Contents
SQLMesh Overview and Core Architecture
Related Pages
1. Project Purpose and Positioning
2. Core Architectural Layers
3. Virtual Data Environments and the Plan Lifecycle
4. Web Server, Lineage, and Extensibility

SQLMesh Overview and Core Architecture

Related topics: Database Engine Adapters and External Integrations, State Management, Migrations, and CI/CD

Source: https://github.com/SQLMesh/sqlmesh / Human Manual

Database Engine Adapters and External Integrations

Related topics: SQLMesh Overview and Core Architecture, State Management, Migrations, and CI/CD

Source: https://github.com/SQLMesh/sqlmesh / Human Manual

LSP, VSCode Extension, and Web UI

Related topics: SQLMesh Overview and Core Architecture

Source: https://github.com/SQLMesh/sqlmesh / Human Manual

State Management, Migrations, and CI/CD

Related topics: SQLMesh Overview and Core Architecture, Database Engine Adapters and External Integrations

Source: https://github.com/SQLMesh/sqlmesh / Human Manual

Doramagic Pitfall Log

Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.

Source: Doramagic discovery, validation, and Project Pack records

AI Context Pack and portable assets

After deciding to continue, take the project context into your own AI host.

Complete pack plus user-owned assets

These files are planning and verification assets for Claude Code, Codex, Gemini, Cursor, ChatGPT, and other AI hosts.

Download complete pack Read Human Manual

BundleComplete Project Pack AssetAI Context Pack AssetBoundary & Risk Card AssetHuman Manual AssetPitfall Log AssetPrompt Preview AssetQuick Start EvidenceREPO_INSPECTION.json

Preflight checks

Treat this page as a planning asset, not proof that your local environment is ready.

The manual is generated from source-linked project files and Doramagic validation signals.
Community evidence warnings stay visible instead of being converted into marketing claims.
This English page is indexable because the locale quality gate passed and explicit English index approval is enabled.
Use the upstream repository as the final authority for installation commands, license, and version-specific behavior.

Pitfall Log and verification risks

Doramagic surfaces high-risk items before users treat a candidate capability as verified.

high

Installation risk requires verification

May increase setup, validation, or first-run risk for the user.

high

Installation risk requires verification

May increase setup, validation, or first-run risk for the user.

high

Configuration risk requires verification

May increase setup, validation, or first-run risk for the user.

high

Capability evidence risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Installation risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Configuration risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Capability evidence risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Maintenance risk requires verification

May increase setup, validation, or first-run risk for the user.