Databend
Unified Multimodal Database for Any Data at Any Scale.
A next-generation cloud-native warehouse built in Rust. Open-source, Snowflake-compatible, and unifying BI, AI, Search, Geo, and Stream.
💡 Why Databend?
Databend is an open-source unified multimodal database built in Rust. It empowers Analytics, AI, Search, and Geo workloads on a single platform directly from object storage.
- Unified Engine: One optimizer and runtime for all data types (Structured, Semi-structured, Vector).
- Native Pipelines: Built-in Stream and Task for automated data cleaning and transformation.
- Cloud Native: Stateless compute nodes over object storage (S3, GCS, Azure) with full ACID support.
- High Performance: Vectorized execution and Zero-Copy processing.
⚡ Quick Start
1. Cloud (Recommended)
Start for free on Databend Cloud - Production-ready in 60 seconds.
2. Local (Python)
Ideal for development and testing:
pip install databend
import databend
ctx = databend.SessionContext()
ctx.sql("SELECT 'Hello, Databend!'").show()
3. Docker
Run the full warehouse locally:
docker run -p 8000:8000 datafuselabs/databend
🚀 Use Cases
- BI & Analytics: High-speed SQL on massive datasets. See Query Processing.
- AI & Vectors: Built-in vector search and embedding management. See Vector Database.
- Full-Text Search: Fast indexing and retrieval on text and semi-structured data (JSON). See JSON Search.
- Geospatial: Advanced geo-analytics and mapping. See Geospatial Analysis.
- Stream & Task: Continuous data ingestion and transformation. See Real-Time ETL.
🤝 Community & Support
Contributors are immortalized in the system.contributors table! 🏆
📄 License
Apache 2.0 + Elastic 2.0 | Licensing FAQ