https://github.com/databendlabs/databend
𝗗𝗮𝘁𝗮, 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 & 𝗔𝗜. Modern alternative to Snowflake. Cost-effective and simple for massive-scale analytics. https://databend.com
https://github.com/databendlabs/databend
ai bigdata database lakehouse olap rust serverless snowflake
Last synced: 20 days ago
JSON representation
𝗗𝗮𝘁𝗮, 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 & 𝗔𝗜. Modern alternative to Snowflake. Cost-effective and simple for massive-scale analytics. https://databend.com
- Host: GitHub
- URL: https://github.com/databendlabs/databend
- Owner: databendlabs
- License: other
- Created: 2020-10-10T06:04:42.000Z (over 5 years ago)
- Default Branch: main
- Last Pushed: 2025-05-10T10:35:58.000Z (10 months ago)
- Last Synced: 2025-05-11T03:47:57.909Z (10 months ago)
- Topics: ai, bigdata, database, lakehouse, olap, rust, serverless, snowflake
- Language: Rust
- Homepage: https://docs.databend.com
- Size: 291 MB
- Stars: 8,407
- Watchers: 96
- Forks: 771
- Open Issues: 589
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Codeowners: .github/CODEOWNERS
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README
Databend
Enterprise Data Warehouse for AI Agents
Large-scale analytics, vector search, full-text search — with flexible agent orchestration and secure Python UDF sandboxes. Built for enterprise AI workloads.
## 💡 Why Databend?
Databend is an open-source enterprise data warehouse built in Rust.
**Core capabilities**: Analytics, vector search, full-text search, auto schema evolution — unified in one engine.
**Agent-ready**: Sandbox UDFs for agent logic, SQL for orchestration, transactions for reliability, branching for safe experimentation on production data.
| | |
| :--- | :--- |
| **📊 Core Engine**
Analytics, vector search, full-text search, auto schema evolution, transactions. | **🤖 Agent-Ready**
Sandbox UDF + SQL orchestration. Build and run agents on your enterprise data. |
| **🏢 Enterprise Scale**
Elastic compute, cloud native. S3/Azure/GCS. | **🌿 Branching**
Git-like data versioning. Agents safely operate on production snapshots. |
## ⚡ Quick Start
### 1. Cloud (Recommended)
[Start for free on Databend Cloud](https://docs.databend.com/guides/cloud/) — Production-ready in 60 seconds.
### 2. Local (Python)
Ideal for development and testing:
```bash
pip install databend
```
```python
import databend
ctx = databend.SessionContext()
ctx.sql("SELECT 'Hello, Databend!'").show()
```
### 3. Docker
Run the full warehouse locally:
```bash
docker run -p 8000:8000 datafuselabs/databend
```
## 🤖 Agent-Ready Architecture
Databend's **Sandbox UDF** enables flexible agent orchestration with a three-layer architecture:
- **Control Plane**: Resource scheduling, permission validation, sandbox lifecycle management
- **Execution Plane** (Databend): SQL orchestration, issues requests via Arrow Flight
- **Compute Plane** (Sandbox Workers): Isolated sandboxes running your agent logic
```sql
-- Define your agent logic
CREATE FUNCTION my_agent(input STRING) RETURNS STRING
LANGUAGE python HANDLER = 'run'
AS $$
def run(input):
# Your agent logic: LLM calls, tool use, reasoning...
return response
$$;
-- Orchestrate agents with SQL
SELECT my_agent(question) FROM tasks;
```
## 🚀 Use Cases
- **AI Agents**: Sandbox UDF + SQL orchestration + branching for safe operations
- **Analytics & BI**: Large-scale SQL analytics — [Learn more](https://docs.databend.com/guides/query/sql-analytics)
- **Search & RAG**: Vector + full-text search — [Learn more](https://docs.databend.com/guides/query/vector-db)
## 🤝 Community & Support
- [📖 Documentation](https://docs.databend.com/)
- [💬 Join Slack](https://link.databend.com/join-slack)
- [🐛 Issue Tracker](https://github.com/databendlabs/databend/issues)
- [🗺️ Roadmap](https://github.com/databendlabs/databend/issues/14167)
**Contributors are immortalized in the `system.contributors` table 🏆**
## 📄 License
[Apache 2.0](licenses/Apache-2.0.txt) + [Elastic 2.0](licenses/Elastic.txt) | [Licensing FAQ](https://docs.databend.com/guides/products/dee/license)
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