KX Supercharges Python Workloads with kdb+ Speed and AI/ML Library Integration

PyKX 3.0 hybrid architecture enhances accessibility and performance for Python-first developers

KX, the leading high-performance analytical database for the AI era, has unveiled upgrades to PyKX, its Python-first interface for kdb+. PyKX 3.0’s hybrid architecture combines the speed and scale of kdb+ with seamless integration to Python’s machine learning (ML) and deep learning libraries, enabling advanced AI-driven algorithms and analytics workflows. Since May 2023, when PyKX became available as an open-source offering, the library has achieved over 400,000 downloads across its distribution channels, underscoring PyKX’s ability to rapidly expand access to the company’s advanced analytics capabilities. The library serves as an essential tool for developers to leverage the benefits of kdb+ and its powerful q programming language for real-time streaming and large-scale historical data-science use cases.

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“With PyKX, Python developers can combine the power of kdb+ with popular ML and AI tools, unlocking new data ingestion and analytics capabilities without changing their workflow. We don’t want to change the way that they think, just the way that they work.”

PyKX is an open-source Python library built and maintained for interoperating with the world’s fastest time-series database, kdb+, and its underlying vector programming language q. With PyKX 3.0, data scientists and engineers can access a true hybrid architecture that empowers users to run high throughput, high-performance, real-time streaming and historical data applications entirely orchestrated from Python.

“If you’re looking for a single piece of technology that can do both historical and real-time analysis, kdb+ is the de facto standard in the trading industry,” said Emanuele Melis, Principal Data Engineer at Talos and KXperts member. “We went through a period where firms were looking for the next big technology that would revolutionize trade analytics, but what we’ve realized is that kdb+ and Python are the two pillars of modern quantitative research.”

Since its release in 2023, PyKX has revolutionized the way developers work with large volumes of time-series data, particularly within quantitative finance. The latest upgrades to PyKX reinforce KX’s commitment to supporting its long-standing Capital Markets customers, enabling Python-first data scientists and quants to accelerate research and trading execution by increasing analytics speed and accelerating the transition to production workloads.

“We are excited about the feature expansions released as part of PyKX,” said Albert Boehm, Technical Lead for the PyKX Platform at Citadel Securities, a leading global market maker and KX customer. “In particular, the addition of a truly Python-first query API will help to make PyKX an attractive default for writing kdb+ based applications. We eagerly anticipate continuing to harness the power and expressiveness of kdb+ through a Pythonic interface, making it accessible and intuitive for quants, developers, and traders across our firm.”

The enhancements to PyKX have been largely influenced by feedback from the KX development community. Version 3.0 is designed to eliminate barriers to entry and streamline workflows. Notable upgrades include:

• Python-First Query API: A familiar API that unifies fast access to both real-time and historical data within Python’s ML environment.
• Python First Streaming Workflows: Allows real-time data handling within the Python ecosystem, making it easier to apply ML and AI models to high-frequency data streams. 95% of tasks can be done fully via Python, removing programming language knowledge gaps.

“When we built PyKX our goal was to better serve the developer community. The inception of PyKX started as an effort to move beyond serving thousands of q developers to expanding access to millions of Python developers. We’ve been able to achieve this growth without compromising the power of kdb+ and q,” said Conor McCarthy, Lead Architect of PyKX at KX. “With PyKX, Python developers can combine the power of kdb+ with popular ML and AI tools, unlocking new data ingestion and analytics capabilities without changing their workflow. We don’t want to change the way that they think, just the way that they work.”