The dream of the "open lakehouse" has always been about freedom — the freedom to own your data and access it from your preferred engines and tools. But even as Apache Iceberg™ makes this a reality, this freedom comes with a hidden "metadata tax."“开放湖仓”的梦想始终围绕着自由——即拥有数据并能通过首选引擎和工具访问数据的自由。然而，尽管 Apache Iceberg™ 让这一梦想成为现实，但这种自由却伴随着隐形的“元数据税”。
If you wanted to use Iceberg tables managed by an external catalog (such as Polaris, Microsoft OneLake, AWS Glue or Unity), you were signing up for a weekend of manual plumbing — juggling IAM roles, mapping schemas and individually creating those Iceberg tables to keep the various catalogs in sync.如果您想使用由外部目录（如 Polaris、Microsoft OneLake、AWS Glue 或 Unity）管理的 Iceberg 表，通常意味着您得花费整个周末进行手动配置——不仅要处理 IAM 角色、映射模式，还要逐个创建 Iceberg 表以保持各目录间的同步。
Today, we are making "open" feel "native." With catalog-linked databases (CLD) and Cortex Code CLI, the data stays exactly where it is; the setup takes seconds; and the insights are just a short conversation away.今天，我们让“开放”体验变得“原生”化。借助目录链接数据库（Catalog-linked databases, CLD）和 Cortex Code CLI，数据将原地留存；设置仅需数秒；而获取洞察只需一段简短的对话。
Catalog-linked databases: The bridge to your data目录链接数据库：通往数据之桥
A catalog-linked database is more than a simple "connection" — it's a dynamic, live and federated link. It allows Snowflake to point directly at an external Iceberg REST catalog and prioritize it to deliver:目录链接数据库不仅仅是一个简单的“连接”，它更像是一个动态、实时且联邦化的链接。它允许 Snowflake 直接指向外部 Iceberg REST 目录，并优先实现以下目标：
- Zero-copy interoperability: Your data lives in your S3 or Azure bucket. You own the bits. Snowflake simply "links" to the metadata.零拷贝互操作性：您的数据存储在您自己的 S3 或 Azure 存储桶中。您拥有这些数据的所有权。Snowflake 仅与元数据建立“链接”。
- Live metadata sync: When a Spark job adds a new column or a Flink stream appends rows to your Iceberg table, it shows up in Snowflake automatically without any additional work.实时元数据同步：当 Spark 作业添加新列或 Flink 流任务向您的 Iceberg 表追加行时，这些更改会自动显示在 Snowflake 中，无需任何额外工作。
- Universal governance: This is the "secret sauce." Even though it is managed by a different catalog, you can still apply Snowflake Horizon policies — like row-level security or data masking — directly to the link, extending your existing governance to virtually your entire data estate without complicated processes.统一治理：这是我们的“秘密武器”。即使数据由其他目录管理，您仍然可以将 Snowflake Horizon 策略（如行级安全或数据脱敏）直接应用于该链接，从而在无需复杂流程的情况下，将现有的治理能力扩展到几乎整个数据资产。
The "easy button": Agentic infrastructure with Cortex Code CLI“一键式”体验：基于 Cortex Code CLI 的智能体基础设施
The most tedious part of the open lakehouse has always been the "plumbing" — setting up external volumes for storage and catalog integrations for metadata. Traditionally, this required a 20-step manual of CLI commands and JSON policy editing.开放湖仓中最繁琐的部分始终是“管道工程”——即配置用于存储的外部卷和用于元数据的目录集成。传统上，这需要一份包含 20 个步骤的手动指南，涉及 CLI 命令和 JSON 策略编辑。
We’ve replaced that manual with Cortex Code Skills. This goes way beyond acting as a chatbot; with Skills, Cortex Code CLI becomes an agentic assistant that understands the complex dependencies of your infrastructure.我们已用 Cortex Code Skills 取代了这些手动操作。这远不止是一个聊天机器人；通过 Skills，Cortex Code CLI 成为了一名能够理解您基础设施复杂依赖关系的智能助手。
The "Cortex Code dividend": Guided, not blind“Cortex Code 红利”：有引导，非盲目
Cortex Code CLI handles the heavy lifting on the Snowflake side while acting as a guide for your cloud provider’s setup. It works with you, rather than doing things in the dark.Cortex Code CLI 负责处理 Snowflake 端的繁重工作，同时为您云服务商的设置提供指导。它与您协同工作，而非让您在盲目中操作。
From days to 60 seconds: For example, tell the CLI: I want to connect my external Iceberg catalog to a new database called 'LAKE_ANALYTICS'.从数天缩短至 60 秒：例如，只需告诉 CLI：“我想将我的外部 Iceberg 目录连接到一个名为 'LAKE_ANALYTICS' 的新数据库。”
In the background, Cortex Code kicks off an agentic workflow:在后台，Cortex Code 会启动一个智能体工作流：
- Snowflake orchestration: It automatically generates and prepares the Snowflake side objects — the external volume, the catalog integration and the CLD — mapping out exactly what is needed.Snowflake 编排：它会自动生成并准备 Snowflake 端的对象——包括外部卷、目录集成和 CLD，并精确规划出所需的一切。
- Guided cloud setup: Since cloud providers require secure human intervention, Cortex Code generates the exact IAM policy and trust relationship snippets you need. It tells you precisely where to paste them in your AWS or Azure console to bridge the gap.引导式云设置：由于云服务商需要安全的人工干预，Cortex Code 会生成您所需的精确 IAM 策略和信任关系代码片段。它会明确告诉您在 AWS 或 Azure 控制台的何处粘贴这些内容，以补全连接。
- Handshake validation: Once you’ve updated your cloud settings, Cortex Code "tests the wires." It validates the connection in real-time to help ensure the metadata is flowing before you ever run your first query.握手验证：在您更新云设置后，Cortex Code 会进行“线路测试”。它会实时验证连接，以确保在您运行第一个查询之前，元数据已经能够正常流动。
The payoff: Talk to all your data, wherever it lives成果：与您的所有数据对话，无论其身在何处
The real magic of a catalog-linked database isn't the setup — it’s the fact that once the connection is live, your lakehouse is immediately accessible for AI-powered insights.目录链接数据库的真正魅力不在于设置过程，而在于一旦连接建立，您的湖仓即可立即用于 AI 驱动的洞察分析。
Because Snowflake understands the context of your external Iceberg tables, you can use Cortex AI agents to bypass SQL entirely. Since the metadata is linked, Snowflake understands the schema, the column comments and the business logic without you having to explain it. Cortex Code CLI goes one step further. It can automatically build semantic views and agents for you for even deeper, richer analytics and recommendations.由于 Snowflake 理解您外部 Iceberg 表的上下文，您可以使用 Cortex AI 智能体完全绕过 SQL。由于元数据已链接，Snowflake 无需您解释即可理解模式、列注释和业务逻辑。Cortex Code CLI 更进一步，它可以自动为您构建语义视图和智能体，从而实现更深入、更丰富的分析与推荐。
The data didn't move. The security didn't break. And your business users didn't have to wait for a data engineer to write a pipeline. And, with Snowflake Intelligence, they can get insights in natural language.数据无需迁移，安全性未受影响，业务用户也无需等待数据工程师编写管道。此外，借助 Snowflake Intelligence，他们还可以通过自然语言获取洞察。
Get started in 5 minutes or less5 分钟内即可上手
You don't need a three-month migration plan to start using CLDs. You just need a prompt.您不需要三个月的迁移计划来开始使用 CLD，只需要一个提示词。
Step 1: Install and link第一步：安装与链接
Install the Cortex Code CLI and tell Cortex: Link my external catalog. Complete the cloud handshake using the snippets Cortex Code provides.安装 Cortex Code CLI 并告知 Cortex：“链接我的外部目录。” 使用 Cortex Code 提供的代码片段完成云端握手。
Step 2: Instant business insights (trends and outliers)第二步：即时业务洞察（趋势与异常）
Once verified, your schemas populate automatically. You can immediately use Snowflake’s intelligence to learn about the business data you just connected. No complex modeling required — just ask:验证完成后，您的模式将自动填充。您可以立即利用 Snowflake 的智能来了解刚刚连接的业务数据。无需复杂的建模，只需提问：
- "What were our top-selling product categories in the external sales lake last month?"“上个月我们外部销售湖中销量最高的产品类别是什么？”
- "Identify any unusual spikes in customer returns from our S3-hosted regional data."“识别我们 S3 托管区域数据中客户退货的任何异常峰值。”
Step 3: Agentic intelligence (recommendations and action)第三步：智能体洞察（推荐与行动）
Ready to turn data into a plan? This is where you activate Snowflake Intelligence on the data you just connected to build a specialized agent. By telling Cortex, "I want to use Snowflake Intelligence on the external catalog I just connected," you move from "What happened?" to "What should I do?"准备好将数据转化为方案了吗？这时您可以在刚连接的数据上激活 Snowflake Intelligence 来构建专业智能体。通过告诉 Cortex：“我想在我刚连接的外部目录上使用 Snowflake Intelligence”，您就能从“发生了什么？”转向“我该怎么做？”
The agent becomes a strategic partner that uses your entire lakehouse data to:该智能体将成为您的战略合作伙伴，利用您整个湖仓的数据来：
- Pinpoint focus: "Based on the inventory trends in the Iceberg lake, which regions are at the highest risk of a stockout next week?"精准定位：“根据 Iceberg 湖中的库存趋势，下周哪些地区出现缺货的风险最高？”
- Make recommendations: "Which customer segment should we target for our upcoming spring promotion based on the purchasing patterns we just connected?"提供推荐：“基于我们刚刚连接的购买模式，我们应该针对哪些客户群体进行即将到来的春季促销？”
- Formulate plans: "Create a step-by-step action plan to improve our delivery times based on the shipping logs in our external tables."制定计划：“根据外部表中的发货日志，制定一份改善我们交付时间的详细行动计划。”
The future is linked未来是互联的
We are moving away from the era of "data warehouses" and "data lakes" and into the era of the connected data estate. By combining the openness and interoperability of Iceberg with the simplicity of Cortex Code Skills, we’re making it possible to manage your entire data estate through a single, simplified and secure conversational control plane.我们正在告别“数据仓库”和“数据湖”时代，迈向互联数据资产时代。通过将 Iceberg 的开放性和互操作性与 Cortex Code Skills 的简洁性相结合，我们使您能够通过一个统一、简化且安全的对话式控制平面来管理整个数据资产。
The "single pane of glass" isn't a dashboard anymore. It’s a prompt. It’s time to stop moving your data and start talking to it.“单一视图”不再是仪表板，而是一个提示词。是时候停止迁移数据，转而与数据直接对话了。
Ready to see Cortex Code CLI in action? Download the Cortex Code CLI and link your first catalog today.准备好体验 Cortex Code CLI 的实际操作了吗？立即下载 Cortex Code CLI 并链接您的第一个目录。
