[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-5520":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":20,"compositeScore":21,"rankGlobal":10,"rankLanguage":10,"license":22,"archived":23,"fork":23,"defaultBranch":24,"hasWiki":23,"hasPages":23,"topics":25,"createdAt":10,"pushedAt":10,"updatedAt":40,"readmeContent":41,"aiSummary":42,"trendingCount":16,"starSnapshotCount":16,"syncStatus":43,"lastSyncTime":44,"discoverSource":45},5520,"databend","databendlabs\u002Fdatabend","databendlabs","Data Agent Ready Warehouse : One for  Analytics, Search, AI, Python Sandbox.  — rebuilt from scratch. Unified architecture on your S3.","https:\u002F\u002Fdocs.databend.com",null,"Rust",9326,885,93,457,0,4,17,48,21,39.84,"Other",false,"main",[26,27,28,29,30,31,32,33,34,35,36,37,38,39],"ai","bigdata","cloud-native","database","elasticsearch","geospatial","lakehouse","olap","rust","serverless","snowflake","sql","vector-database","vector-search","2026-06-12 02:01:11","\u003Ch1 align=\"center\">Databend\u003C\u002Fh1>\n\u003Ch3 align=\"center\">Enterprise Data Warehouse for AI Agents\u003C\u002Fh3>\n\u003Cp align=\"center\">Large-scale analytics, vector search, full-text search — with flexible agent orchestration and secure Python UDF sandboxes. Built for enterprise AI workloads.\u003C\u002Fp>\n\n\u003Cdiv align=\"center\">\n\n\u003Ca href=\"https:\u002F\u002Fdatabend.com\u002F\">☁️ Try Cloud\u003C\u002Fa> •\n\u003Ca href=\"#-quick-start\">🚀 Quick Start\u003C\u002Fa> •\n\u003Ca href=\"https:\u002F\u002Fdocs.databend.com\u002F\">📖 Documentation\u003C\u002Fa> •\n\u003Ca href=\"https:\u002F\u002Flink.databend.com\u002Fjoin-slack\">💬 Slack\u003C\u002Fa>\n\n\u003Cbr>\u003Cbr>\n\n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fdatabendlabs\u002Fdatabend\u002Factions\u002Fworkflows\u002Frelease.yml\">\n\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Factions\u002Fworkflow\u002Fstatus\u002Fdatafuselabs\u002Fdatabend\u002Frelease.yml?branch=main\" alt=\"CI Status\" \u002F>\n\u003C\u002Fa>\n\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPlatform-Linux%2C%20macOS%2C%20ARM-green.svg?style=flat\" alt=\"Platform\" \u002F>\n\n\u003C\u002Fdiv>\n\n\u003Cbr>\n\n\u003Cimg src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F4c288d5c-9365-44f7-8cde-b2c7ebe15622\" alt=\"databend\" width=\"100%\" \u002F>\n\n## 💡 Why Databend?\n\nDatabend is an open-source enterprise data warehouse built in Rust.\n\n**Core capabilities**: Analytics, vector search, full-text search, auto schema evolution — unified in one engine.\n\n**Agent-ready**: Sandbox UDFs for agent logic, SQL for orchestration, transactions for reliability, branching for safe experimentation on production data.\n\n| | |\n| :--- | :--- |\n| **📊 Core Engine**\u003Cbr>Analytics, vector search, full-text search, auto schema evolution, transactions. | **🤖 Agent-Ready**\u003Cbr>Sandbox UDF + SQL orchestration. Build and run agents on your enterprise data. |\n| **🏢 Enterprise Scale**\u003Cbr>Elastic compute, cloud native. S3\u002FAzure\u002FGCS. | **🌿 Branching**\u003Cbr>Git-like data versioning. Agents safely operate on production snapshots. |\n\n![Databend Architecture](https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F288dea8d-0243-4c45-8d18-d4d402b08075)\n\n## ⚡ Quick Start\n\n### 1. Cloud (Recommended)\n[Start for free on Databend Cloud](https:\u002F\u002Fdocs.databend.com\u002Fguides\u002Fcloud\u002F) — Production-ready in 60 seconds.\n\n### 2. Local (Python)\nIdeal for development and testing:\n\n```bash\npip install databend\n```\n\n```python\nimport databend\nctx = databend.SessionContext()\nctx.sql(\"SELECT 'Hello, Databend!'\").show()\n```\n\n### 3. Docker\nRun the full warehouse locally:\n\n```bash\ndocker run -p 8000:8000 datafuselabs\u002Fdatabend\n```\n\n## 🤖 Agent-Ready Architecture\n\nDatabend's **Sandbox UDF** enables flexible agent orchestration with a three-layer architecture:\n\n- **Control Plane**: Resource scheduling, permission validation, sandbox lifecycle management\n- **Execution Plane** (Databend): SQL orchestration, issues requests via Arrow Flight\n- **Compute Plane** (Sandbox Workers): Isolated sandboxes running your agent logic\n\n```sql\n-- Define your agent logic\nCREATE FUNCTION my_agent(input STRING) RETURNS STRING\nLANGUAGE python HANDLER = 'run'\nAS $$\ndef run(input):\n    # Your agent logic: LLM calls, tool use, reasoning...\n    return response\n$$;\n\n-- Orchestrate agents with SQL\nSELECT my_agent(question) FROM tasks;\n```\n\n## 🚀 Use Cases\n\n- **AI Agents**: Sandbox UDF + SQL orchestration + branching for safe operations\n- **Analytics & BI**: Large-scale SQL analytics — [Learn more](https:\u002F\u002Fdocs.databend.com\u002Fguides\u002Fquery\u002Fsql-analytics)\n- **Search & RAG**: Vector + full-text search — [Learn more](https:\u002F\u002Fdocs.databend.com\u002Fguides\u002Fquery\u002Fvector-db)\n\n## 🤝 Community & Support\n\n- [📖 Documentation](https:\u002F\u002Fdocs.databend.com\u002F)\n- [💬 Join Slack](https:\u002F\u002Flink.databend.com\u002Fjoin-slack)\n- [🐛 Issue Tracker](https:\u002F\u002Fgithub.com\u002Fdatabendlabs\u002Fdatabend\u002Fissues)\n- [🗺️ Roadmap](https:\u002F\u002Fgithub.com\u002Fdatabendlabs\u002Fdatabend\u002Fissues\u002F14167)\n\n**Contributors are immortalized in the `system.contributors` table 🏆**\n\n## 📄 License\n\n[Apache 2.0](licenses\u002FApache-2.0.txt) + [Elastic 2.0](licenses\u002FElastic.txt) | [Licensing FAQ](https:\u002F\u002Fdocs.databend.com\u002Fguides\u002Fproducts\u002Fdee\u002Flicense)\n\n---\n\n\u003Cdiv align=\"center\">\n\u003Cstrong>Enterprise warehouse, agent ready\u003C\u002Fstrong>\u003Cbr>\n\u003Ca href=\"https:\u002F\u002Fdatabend.com\">🌐 Website\u003C\u002Fa> •\n\u003Ca href=\"https:\u002F\u002Fx.com\u002FDatabendLabs\">🐦 Twitter\u003C\u002Fa>\n\u003C\u002Fdiv>","Databend 是一个专为企业级AI工作负载设计的数据仓库。它集成了大规模数据分析、向量搜索和全文搜索等功能，并支持灵活的代理编排及安全的Python UDF沙箱环境，所有这些都基于统一的架构之上。该工具采用Rust语言构建，具有高性能与高安全性特点，能够无缝对接S3等对象存储服务，适用于需要处理复杂数据查询、分析任务以及构建AI应用的企业场景。此外，Databend还提供了类似Git的数据版本控制功能，允许用户在生产数据快照上安全地进行实验。",2,"2026-06-11 03:03:45","top_language"]