Kx and the Internet of Things Asia

21 Apr 2017 | , , , ,

Adoption of connected devices and Internet of Things data analysis has become a compelling business imperative for companies and countries around the world. In Asia, the IoT revolution has unique characteristics reflecting the infrastructure and politics of the region. The conference is fittingly held in Singapore, which is striving to become the world's first Smart City.

Enhancing Your kdb+/q Toolkit: Real World Examples of Adverbs

12 Apr 2017 | , , , ,

Nuša Žnuderl's latest blog post uses five real-world examples to demonstrate how kdb+/q coders can improve their results by using adverbs and not using looping constructs. Long-term the benefit is vastly improved performance from doing things in the “q way.” In her blog Nuša writes: "Similar to the English language, adverbs in q augment operations to allow an application on lists. They make code shorter, clearer and almost always more efficient than the alternative loopy modus operandi – all of which are qualities that differentiate code written by proficient q users from the rest."

Kx 1.1 billion taxi ride benchmark highlights advantages of kdb+ architecture

25 Jan 2017 | , , ,

Stellar performance in third-party benchmarks is a tradition at Kx, and now we can add a new benchmark to the list, the taxi ride benchmark developed by Mark Litwintschik. This latest benchmark queries a 1.1 billion New York City taxi ride dataset. Our results were over four orders of magnitude faster than any other CPU technology and comparable to GPU-based code.

GitHub: Machine learning project for kdb+/q

14 Dec 2016 | , , ,

Software engineer and kdb+ programmer Juan Lasheras recently added a kdb+/q machine learning project to GitHub. The aim of Juan's ml.q repository is to act as a multi-purpose machine learning toolkit. It provides multiple useful methods that practitioners can use for data analysis and predictive modeling. It is comparable to the scikit-learn toolkit for Python. Check out his repo on GitHub to see the algorithms he implemented.

Research in kdb+/q: AQuery

29 Sep 2016 | , , ,

Dr. Dennis Shasha, of the Courant Institute of Mathematical Sciences at NYU, and José Pablo Cambronero, a PhD student at MIT, recently presented the results of their research on AQuery and q/kdb+ at the latest Kx Community NYC Meetup. AQuery is a simple extension to SQL that makes joins, moving averages, correlations, and other such