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fix: i18n and links (#2920)
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docs/cn/guides/00-products/index.md

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**Databend** —— 一套引擎撑起所有数据与场景
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**Databend** —— **一套引擎撑起所有数据与场景(ANY DATA. ANY SCALE. ONE DATABASE).**
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Databend 是开源的云原生数仓,把存储、向量搜索、SQL 分析、全文检索与地理计算统一到一套与 Snowflake 兼容的 SQL 接口上。所有数据都放在对象存储里,写入、分析、搜索一次到位,无需折腾多套系统。
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**Databend 是开源的**云原生数仓,把存储、向量搜索、SQL 分析、全文检索与地理计算统一到一套与**Snowflake 兼容的 SQL 接口上**。所有数据都放在对象存储里写入、分析、搜索一次到位无需折腾多套系统。
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想上手随时可行:可以直接开通 Databend Cloud,也能本地用 Docker 自建,甚至 `pip install databend` 嵌到现有工程——不论入口如何,运行的都是同一份内核
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[**GitHub**](https://github.com/databendlabs/databend) 上探索其引擎。您可以通过 [**Databend Cloud**](https://www.databend.cn/)`docker run` `pip install databend` 启动它,每种方式都在您的对象存储上运行着同一个统一的引擎
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**Open-source** datastore, vector, analytics, search, and geospatial engines converge on one **Snowflake-compatible SQL surface** so teams store anything, search everything, power semantic workloads, and deliver real-time insights without moving data.
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Explore the engine on [**GitHub**](https://github.com/databendlabs/databend). Launch in Databend Cloud, `docker run`, or `pip install databend`—every option runs the same unified engine on your object store.
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Explore the engine on [**GitHub**](https://github.com/databendlabs/databend). Launch in [**Databend Cloud**](https://www.databend.com/), `docker run`, or `pip install databend`—every option runs the same unified engine on your object store.
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<DocsOverview />
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**推荐先从这些主题开始了解**
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**快速上手**
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- **[快速开始](/guides/deploy/quickstart)**: 用 Docker 几分钟内启动 Databend,并加载示例数据。
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- **[Databend Cloud](/guides/cloud)**: 创建无服务器仓库,集中管理组织与资源。
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- **[快速开始](/guides/deploy/quickstart)**: 用 Docker 几分钟内启动 Databend,并加载示例数据。
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- **[Databend Cloud](/guides/cloud)**: 创建无服务器仓库,集中管理组织与资源。
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- **[连接到 Databend](/guides/sql-clients)**: 通过常见 SQL 客户端或编程语言接入 Databend。
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- **[SQL 参考](/sql)**: 查询 Databend 支持的 SQL 命令、函数与语法。
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**数据处理**
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- **[数据加载](/guides/load-data)**: 把不同来源的数据导入 Databend。
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- **[数据卸载](/guides/unload-data)**: 将 Databend 数据导出为所需格式。
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- **[半结构化数据](/sql/sql-functions/semi-structured-functions)**: 借助 VARIANT 处理 JSON、数组与嵌套结构。
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**统一引擎场景**
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- **[SQL 分析指南](/guides/query/sql-analytics)**: 用同一套引擎支撑分析、搜索、向量与地理任务。
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- **[JSON 与搜索指南](/guides/query/json-search)**: 依托倒排索引和 Elasticsearch 风格 `QUERY` 检索 VARIANT 载荷。
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- **[向量数据库指南](/guides/query/vector-db)**: 在 Databend 内存储嵌入并完成语义相似检索。
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- **[地理分析指南](/guides/query/geo-analytics)**: 借助地理空间 SQL 绘制事件地图,实时定位热点。
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- **[湖仓 ETL 指南](/guides/query/lakehouse-etl)**: 将对象存储文件流式写入托管表,杜绝数据孤岛。
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- **[地理分析指南](/guides/query/geo-analytics)**: 借助地理空间 SQL 绘制事件地图实时定位热点。
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- **[湖仓 ETL 指南](/guides/query/lakehouse-etl)**: 将对象存储文件流式写入托管表杜绝数据孤岛。
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**性能与扩展**
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- **[性能优化](/guides/performance)**: 结合多种策略加速查询与计算。
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- **[基准测试](/guides/benchmark)**: 了解 Databend 与其他数据仓库的性能对比。
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- **[数据湖仓](/sql/sql-reference/table-engines)**: 与 Hive、Iceberg、Delta Lake 无缝协作。
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**社区与支持**
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- **[加入 Slack](https://link.databend.com/join-slack)**: 与社区成员及核心工程师直接交流。
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- **[文档问题](https://github.com/databendlabs/databend-docs/issues)**: 反馈文档缺失或提交改进建议。
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- **[路线图](https://github.com/databendlabs/databend/issues/14167)**: 跟踪即将发布的功能并留下意见。

docs/en/guides/00-products/index.md

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**Databend** —— ANY DATA. ANY SCALE. ONE DATABASE.
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**Databend** —— **一套引擎撑起所有数据与场景(ANY DATA. ANY SCALE. ONE DATABASE).**
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内置存储、向量、分析、搜索与地理空间引擎共享一套 Snowflake 兼容 SQL 接口,让团队可以存任何数据、查任何内容、驱动语义工作负载,并实时交付洞察而无需搬运数据
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**Databend 是开源的**云原生数仓,把存储、向量搜索、SQL 分析、全文检索与地理计算统一到一套与**Snowflake 兼容的 SQL 接口上**。所有数据都放在对象存储里,写入、分析、搜索一次到位,无需折腾多套系统
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无论是 Databend Cloud、Docker 自托管还是 `pip install databend`,统一引擎都直接运行在你的对象存储之上
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[**GitHub**](https://github.com/databendlabs/databend) 上探索其引擎。您可以通过 [**Databend Cloud**](https://www.databend.cn/)`docker run``pip install databend` 启动它,每种方式都在您的对象存储上运行着同一个统一的引擎
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**Open-source** datastore, vector, analytics, search, and geospatial engines converge on one **Snowflake-compatible SQL surface** so teams store anything, search everything, power semantic workloads, and deliver real-time insights without moving data.
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Explore the engine on [**GitHub**](https://github.com/databendlabs/databend). Launch in Databend Cloud, `docker run`, or `pip install databend`—every option runs the same unified engine on your object store.
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Explore the engine on [**GitHub**](https://github.com/databendlabs/databend). Launch in [**Databend Cloud**](https://www.databend.com/), `docker run`, or `pip install databend`—every option runs the same unified engine on your object store.
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**Here are some entries you might want to learn about**
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**Getting Started**
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- **[Quick Start](/guides/deploy/quickstart)**: Launch Databend with Docker and load sample data fast.
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- **[Databend Cloud](/guides/cloud)**: Spin up serverless warehouses and manage your organization.
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- **[Connect to Databend](/guides/sql-clients)**: Connect with various SQL clients and programming languages.
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- **[SQL Reference](/sql)**: Browse Databend SQL commands, functions, and syntax.
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**Data Processing**
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- **[Data Loading](/guides/load-data)**: Import data from various sources into Databend.
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- **[Data Unloading](/guides/unload-data)**: Export data from Databend to different formats.
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- **[Semi-Structured Data](/sql/sql-functions/semi-structured-functions)**: Process JSON, arrays, and nested data with VARIANT type.
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**Unified Workloads**
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- **[SQL Analytics Guide](/guides/query/sql-analytics)**: Shared session tables for analytics, search, vector, and geo workloads.
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- **[JSON & Search Guide](/guides/query/json-search)**: Query VARIANT payloads with inverted indexes and Lucene-style `QUERY`.
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- **[Vector Database Guide](/guides/query/vector-db)**: Store embeddings and run semantic similarity inside Databend.
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- **[Geo Analytics Guide](/guides/query/geo-analytics)**: Map incidents with geospatial SQL for real-time insights.
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- **[Lakehouse ETL Guide](/guides/query/lakehouse-etl)**: Stream object storage files into managed tables without silos.
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**Performance & Scale**
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- **[Performance Optimization](/guides/performance)**: Enhance query performance with various strategies.
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- **[Benchmarks](/guides/benchmark)**: Compare Databend performance with other data warehouses.
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- **[Data Lakehouse](/sql/sql-reference/table-engines)**: Seamless integration with Hive, Iceberg, and Delta Lake.
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**Community & Support**
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- **[Join Slack](https://link.databend.com/join-slack)**: Chat with the Databend community and core engineers.
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- **[Docs Issues](https://github.com/databendlabs/databend-docs/issues)**: Report problems or request new coverage.
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- **[Roadmap](https://github.com/databendlabs/databend/issues/14167)**: Track upcoming features and share feedback.

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