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 pandas.

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. More

JIT Compile ⚡

A runtime compiler embedded in the library optimizes your code. More

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.Get started

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. More

Benchmarks 📈

FireDucks shows high performance gain while executing various queries included in the TPC-H and TPCx-BB benchmarks. More.

Use Cases

Automobile

Telecom

Finance

Cloud Hosting

E Commerce

Gaming

From Users

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TTDC

Toyota Technical Development Corporation has seen significant benefits within about three months of the introduction of the system.

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NEC Solution Innovators

NEC Solution Innovators, Ltd. has used FireDucks for a data analysis task.

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From Developers

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How to run polars-tpch benchmark with FireDucks

By Kazuhisa Ishizaka | 2024-12-06

Recently we have updated the result of polars-tpch benchmark with FireDucks. This post describes how to reproduce it.

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FireDucks optimization helps you process larger-than-memory-dataset

By Sourav Saha | 2024-12-05

This article explains how FireDucks can efficienly optimize data loading when only a few columns are to be processed in a query

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Efficient caching in FireDucks Lazy Execution

By Sourav Saha | 2024-12-05

This article explains how FireDucks lazy-execution caches intermediate results to be used at later stage

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What to do when FireDucks is slow

By Masashi Kotera | 2024-11-11

This article describes possible causes and remedies for slow programs using FireDucks.

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