Empower your teams with real-time and historical data insights using Python

Introducing PyKX

PyKX integrates the powerful kdb+ database with Python, providing a seamless bridge to build high-performance analytics applications.It unlocks the time-series processing and real-time capabilities of kdb+ for Python users, enabling them to solve complex data challenges with ease.Whether you’re a data scientist, engineer, or analyst, PyKX empowers you to leverage cutting-edge analytics and machine learning within the familiar Python ecosystem.

Benefits

Democratized access

Empower Python users to leverage kdb+ without q expertise, enabling real-time analytics across broader teams (data scientists, engineers, and analysts).

10x Faster analytics

Accelerate time-series data processing for real-time insights, achieving results in milliseconds for faster, data-driven decision-making.

Simplified interoperability

Consolidate tech stacks with a single solution for seamless, high-speed integration between Python and kdb+, reducing costs and complexity.

Scalable workflows

Maintain high performance with scalable Python workflows, effortlessly meeting the demands of growing datasets and workloads.

Why choose PyKX?

PYKX allows developers to leverage their existing skills and drive maximum value from KX technology straight away — efficiently executing any model-centric application, from simulation testing to machine learning and optimization.

Lower barrier to entry

Harness the power of q with ease! PyKX lets developers use a simpler programming language and skills they already possess, while still leveraging q’s high performance.

High versatility

Supporting a wide variety of data formats and sources, PyKX scales efficiently to handle increasing data volumes and integrates with cloud services or on-premise solutions.

More efficient analytics

Access slimline Python apps 80x faster thanks to PyKX’s management of in-memory or on-disk objects to optimize interactions between technologies.