About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

KX Releases PyKX Python Interface to kdb+ for Developer Community, Accelerates Data Science Workflows

Subscribe to our newsletter

KX, provider of the kdb+ time-series database, Data Timehouse, and KDB.AI vector database, has released a new version of PyKX, its Python first interface to kdb+, with a development-only licence. The release expands the reach of KX technology to the more than 10 million strong Python developer community.

By giving Python developers the ability to accelerate data, math, and analytics intensive applications for real-time insights across all Python workloads, PyKX can streamline traditional data science workflows by bundling advanced connectivity, vector encodings, built in algorithms and powerful data organisational tools that accelerate complex processing at scale while simplifying data exploration. Other use cases include anomaly detection, predictive maintenance, feature engineering, back testing, and quantitative finance.

“We’re on a mission to democratise access to our technologies,” says Ashok Reddy, CEO of KX. “With this release, we’re giving Python developers and data professionals the ability to run analytics and AI workloads on the industry’s fastest time series and vector database using the world’s most popular language and programming environment for data science.”

Kdb+ user Jonny Press, CTO at Data Intellect, comments: “PyKX is a game changer for enterprises looking to put kdb+ alongside Python for developer and data science teams. Many of our clients use the languages in tandem, but the question has always been where the boundary lies, which parts of the workload do you do in kdb+ and when do you shift to Python. With PyKX there is no boundary.”

PyKX is available initially on PyPI, a repository of software for the Python programming language. To get started and learn how Python interoperates with kdb+, a prebuilt Jupyter project hub has been created giving access to a working Jupyter Notebook preloaded with KX software and KX training materials. Users can then download PyKX and use it with an existing kdb+ licence, a free trial, or a kdb+ Insights Personal Edition.

Subscribe to our newsletter

Related content

WEBINAR

Upcoming Webinar: Data platform modernisation: Best practice approaches for unifying data, real time data and automated processing

Date: 17 March 2026 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes Financial institutions are evolving their data platform modernisation programmes, moving beyond data-for-cloud capabilities and increasingly towards artificial intelligence-readiness. This has shifted the data management focus in the direction of data unification, real-time delivery and automated governance. The drivers of...

BLOG

Past, Present, and Future of AI and Machine Learning in Trading and Investment Management

On this episode of FinTech Focus TV recorded at A-Team Group’s Buy AND Build Summit, Toby Babb of Harrington Starr sits down with David Marcos, Founder and Managing Partner at Quantoro Technologies, to explore how AI agents are redefining trading, portfolio management, and the investor experience. From simplifying complex investment strategies to the rise of...

EVENT

Eagle Alpha Alternative Data Conference, Spring, New York, hosted by A-Team Group

Now in its 8th year, the Eagle Alpha Alternative Data Conference managed by A-Team Group, is the premier content forum and networking event for investment firms and hedge funds.

GUIDE

Regulatory Data Handbook 2025 – Thirteenth Edition

Welcome to the thirteenth edition of A-Team Group’s Regulatory Data Handbook, a unique and practical guide to capital markets regulation, regulatory change, and the data and data management requirements of compliance across Europe, the UK, US and Asia-Pacific. This year’s edition lands at a moment of accelerating regulatory divergence and intensifying data focused supervision. Inside,...