Compiler Accelerated DataFrame Library for Python with fully-compatible pandas API
import fireducks.pandas as pd
Accelerate pandas without any manual code changes
Do you have a pandas-based program that is slow? FireDucks can speed-up your programs without any manual code changes. You can accelerate your data analysis without worrying about slow performance due to single-threaded execution in panda
Sustainable and Economical
Concerned about the cost and environmental impact of cloud computing? Our acceleration technology reduces cloud usage fees, while minimizing the CO2 emissions at the same time, making FireDucks an environment-friendly and wallet-friendly choice.
Reliability and Performance
FireDucks is developed by infusing the essence of supercomputers that NEC has refined over the years. Made in Japan, high-quality FireDucks promises reliability and high performance.
Features
Multithreaded ✨
FireDucks is multi-threaded, enabling higher speeds on multi-core CPUs
JIT Compile ⚡
A runtime compiler embedded in the library optimizes your code
pandas API 🐼
FireDucks is fully compatible with pandas API. The only difference is the import statement. No additional learning is required to start with FireDucks
AS IS Execution 🚀
You can run your pandas program directly with FireDucks. Its import-hook functionality will automatically replace the import statement for pandas with the import statement for FireDucks
Benchmarks 📈
FireDucks shows high performance gain while executing various queries included in the TPC-H and TPCx-BB benchmarks
references:
https://fireducks-dev.github.io/
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