Atlas 是一款语言无关的工具，用于管理和迁移数据库模式，采用现代 DevOps 原则。 它提供两种工作流程：

• 声明式：类似于Terraform，Atlas将数据库当前状态与期望状态进行比较，如下 定义在 [HCL]、[SQL] 或 [ORM] 模式中。基于该比较，它生成并执行迁移计划 将数据库转换到其期望状态。

• 版本化：与其他工具不同，Atlas 会自动为你规划模式迁移。用户可以描述他们想要的 数据库模式中[HCL]、[SQL]或他们选择的[ORM]，通过利用Atlas，他们可以规划、lint并应用 必要的数据库迁移。

支持的数据库

PostgreSQL · MySQL · MariaDB · SQL Server · SQLite · 点击屋· 红移· 神谕者· 雪花· 蟑螂数据库 · TiDB · 数据砖 · 扳手· Aurora DSQL · Azure Fabric

安装

macOS + Linux：

自制内容：

Docker：

NPM：

请参阅所有平台的安装文档。

安装技能

克劳德代码：

Codex、Cursor 或 GitHub Copilot，从你的仓库根节点开始：

[!注] 地图集网站拥有最新版本

Atlas - Manage Your Database Schema as Code

Atlas is a language-agnostic tool for managing and migrating database schemas using modern DevOps principles. It offers two workflows:

• Declarative: Similar to Terraform, Atlas compares the current state of the database to the desired state, as defined in an [HCL], [SQL], or [ORM] schema. Based on this comparison, it generates and executes a migration plan to transition the database to its desired state.

• Versioned: Unlike other tools, Atlas automatically plans schema migrations for you. Users can describe their desired database schema in [HCL], [SQL], or their chosen [ORM], and by utilizing Atlas, they can plan, lint, and apply the necessary migrations to the database.

Supported Databases

PostgreSQL · MySQL · MariaDB · SQL Server · SQLite · ClickHouse · Redshift · Oracle · Snowflake · CockroachDB · TiDB · Databricks · Spanner · Aurora DSQL · Azure Fabric

Installation

macOS + Linux:

curl -sSf https://atlasgo.sh | sh

Homebrew:

brew install ariga/tap/atlas

Docker:

docker pull arigaio/atlas

NPM:

npx @ariga/atlas

See installation docs for all platforms.

Install the skills

Claude Code:

claude plugin marketplace add ariga/atlas
claude plugin install atlas@ariga

Codex, Cursor, or GitHub Copilot, from the root of your repository:

npx skills add ariga/atlas -a codex -y   # or: -a cursor, -a github-copilot

[!NOTE] The Atlas website has the most up-to-date version of these skills: they are maintained there and copied to skills/ from time to time.

Key Features