A high-performance columnar vector database written in pure C. RayforceDB combines the power of columnar storage with SIMD vectorization to deliver fast analytics on time-series and big data workloads.
- Columnar storage with vectorized operations for analytical workloads
- Minimal footprint: <1Mb binary, zero dependencies
- Cross-platform: Linux, macOS, Windows, WebAssembly
- Simple query language: Lisp-like Rayfall syntax, no complex SQL
- Custom memory management: Parallel lockfree buddy allocator optimized for analytical workloads
git clone https://github.com/singaraiona/rayforce.git
cd rayforce
make release
./rayforce- Financial analytics and high-frequency trading data
- IoT sensor data and time-series monitoring
- Real-time analytics and streaming data
- Embedded systems and edge computing
- Data science and exploratory analysis
- LLMs and semantic retrieval
make debug # Debug build with sanitizers
make release # Optimized production build
make tests # Run test suite
make bench # Run benchmark suiteRayforce has powerful Python bindings (beta stage, but contributions are welcome)
Contributions are welcome! You can help by:
- Reporting bugs and requesting features via GitHub Issues
- Submitting pull requests
- Creating example scripts and use cases
- Improving documentation
RayforceDB is jointly developed with and sponsored by Lynx.
This partnership has been instrumental in making RayforceDB a mature, production-ready database system. Lynx Capital's active involvement in development and their commitment to innovative open-source technologies in the financial sector has enabled RayforceDB to reach its full potential.