base on 𝗔𝗜-𝗡𝗮𝘁𝗶𝘃𝗲 𝗗𝗮𝘁𝗮 𝗪𝗮𝗿𝗲𝗵𝗼𝘂𝘀𝗲. Open-source Snowflake alternative. Proven at petabyte scale with enterprise performance. Built for multimodal analytics. https://databend.com <h1 align="center">Databend</h1> <h2 align="center">ANY DATA. ANY SCALE. ONE DATABASE.</h2> <h3 align="center">Multimodal data warehouse for the AI era with Snowflake-compatible SQL</h3> <div align="center"> <a href="https://databend.com/">☁️ Try Cloud</a> • <a href="#quick-start">🚀 Quick Start</a> • <a href="https://docs.databend.com/">📖 Documentation</a> <br><br> <a href="https://link.databend.com/join-slack"> <img src="https://img.shields.io/badge/slack-databend-0abd59?logo=slack" alt="slack" /> </a> <a href="https://github.com/databendlabs/databend/actions/workflows/release.yml"> <img src="https://img.shields.io/github/actions/workflow/status/datafuselabs/databend/release.yml?branch=main" alt="CI Status" /> </a> <img src="https://img.shields.io/badge/Platform-Linux%2C%20macOS%2C%20ARM-green.svg?style=flat" alt="Platform" /> </div> <br> <img src="https://github.com/databendlabs/databend/assets/172204/9997d8bc-6462-4dbd-90e3-527cf50a709c" alt="databend" /> ## Why Databend? **Multimodal Data Warehouse**: Analyze structured, semi-structured, vector, and geospatial data with unified Snowflake-compatible SQL. **AI-Native Platform**: Built-in vector search, AI functions, embedding generation, and full-text search - no separate systems needed. **10x Faster & 90% Cost Reduction**: Rust-powered vectorized execution with S3-native storage eliminates vendor lock-in and proprietary overhead. **Deploy Anywhere, Connect Everything**: 100% open source - run locally with `pip install databend`, self-host, or use managed cloud clusters. All instances share the same data seamlessly. **Production Proven**: Trusted by world-class enterprises managing 800+ petabytes and 100+ million queries daily. **Enterprise Ready**: Fine-grained access control, data masking, and audit logging with complete data sovereignty. ## Quick Start ### Option 1: Databend Cloud Warehouse (Recommended) [Start with Databend Cloud](https://docs.databend.com/guides/cloud/) - Serverless warehouse clusters, production-ready in 60 seconds ### Option 2: Local Development with Python ```bash pip install databend ``` ```python import databend ctx = databend.SessionContext() # Local table for quick testing ctx.sql("CREATE TABLE products (id INT, name STRING, price FLOAT)").collect() ctx.sql("INSERT INTO products VALUES (1, 'Laptop', 1299.99), (2, 'Phone', 899.50)").collect() ctx.sql("SELECT * FROM products").show() # S3 remote table (same as cloud warehouse) ctx.create_s3_connection("s3", "your_key", "your_secret") ctx.sql("CREATE TABLE sales (id INT, revenue FLOAT) 's3://bucket/sales/' CONNECTION=(connection_name='s3')").collect() ctx.sql("SELECT COUNT(*) FROM sales").show() ``` ### Option 3: Docker (Self-Host Experience) ```bash docker run -p 8000:8000 datafuselabs/databend ``` Experience the full warehouse capabilities locally - same features as cloud clusters. ## Benchmarks **Performance**: [TPC-H vs Snowflake](https://docs.databend.com/guides/benchmark/tpch) | [ClickBench Results](https://www.databend.com/blog/category-product/clickbench-databend-top) **Cost**: [90% Cost Reduction](https://docs.databend.com/guides/benchmark/data-ingest) ## Architecture  **Multimodal Cloud Warehouse**: Production clusters analyze structured, semi-structured, vector, and geospatial data with Snowflake-compatible SQL. Local development environments can attach to the same warehouse data for seamless development. ## Use Cases - **Data Analytics**: Snowflake alternative with significant cost reduction - **AI/ML Pipelines**: Vector search and AI functions built-in - **Real-time Analytics**: High-performance queries on petabyte-scale data - **Data Lake Analytics**: Query Parquet, CSV, TSV, NDJSON, Avro, ORC directly from S3 ## Community - [📖 Documentation](https://docs.databend.com/) - Complete guides and references - [💬 Slack](https://link.databend.com/join-slack) - Live community discussion - [🐛 GitHub Issues](https://github.com/databendlabs/databend/issues) - Bug reports and feature requests - [🎯 Good First Issues](https://link.databend.com/i-m-feeling-lucky) - Start contributing today **Contributors get immortalized in `system.contributors` table! 🏆** ## 📄 License [Apache License 2.0](licenses/Apache-2.0.txt) + [Elastic License 2.0](licenses/Elastic.txt) [Licensing FAQs](https://docs.databend.com/guides/products/dee/license) --- <div align="center"> <strong>Built by engineers who redefine what's possible with data</strong><br> <a href="https://databend.com">🌐 Website</a> • <a href="https://x.com/DatabendLabs">🐦 Twitter</a> • <a href="https://github.com/databendlabs/databend/issues/14167">🗺️ Roadmap</a> </div> ", Assign "at most 3 tags" to the expected json: {"id":"2543","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"