Turbocharge Python Workloads with the Simplicity, Speed, and Scale of kdb

Python-first
Using q?
Learn More
Get Started

In two decades, the Python programming language has transformed data science. As a versatile programming language, Python’s SciPy Stack – with NumPy, MatPlotlib and Pandas – has provided a core foundation for transformative machine and deep learning and data science. Revolutionary libraries and platforms like SciKitlearn, Tensorflow, Prophet, and Keras, with collaborative research-friendly utilities like the Jupyter Notebook helps Python make the AI world go around.

Kdb – the world’s most powerful, lightweight, and simple time series database and analytics engine – offers integrated Python interoperability to accelerate data, math, and analytics-intensive applications. This enables data application developers to benefit from real-time insights across all Python workloads.

Icon illustrating simplicity - KX

From the Zen of Python, “Simple is better than complex.”

Proven in the toughest of data environments and used by leading global investment banks and data-driven businesses worldwide, kdb is available today for all your Machine Learning and AI time series demands in Python.

PYTHON-FIRST FOR MAXIMUM IMPACT, AND FULL SQL SUPPORT

BRING THE POWER OF THE WORLD’S FASTEST TIME SERIES DATABASE AND ANALYTICS ENGINE TO YOUR PYTHON CODE AND JUPYTER NOTEBOOKS WITH KDB INSIGHTS AND KDB INSIGHTS ENTERPRISE.

PERFORMANCE

Seamlessly deliver 100x more data and model performance to your Notebooks and Python code.

EASE OF USE

Simply expose Python libraries and objects like Pandas and NumPy to the power of q and kdb.

TIME TO VALUE

Productionize research by running full-resolution data and real-time analytics directly in your notebooks.

Introduction to PyKX Training Course

To get started and learn how Python interoperates with KX Insights and KX Insights Enterprise, our prebuilt Project JupyterHub gives you access to a working Jupyter Notebook pre-loaded with KX software and KX training materials, no installation required. On authenticating your email, you can engage with the short Introduction to PyKX Training Course and test how much more you can do with Python and KX together!

See PyKX Training