-
KX Product Insights: What’s in a Baby Name?
15 1月, 2019
-
How to avoid a goat in Monte Carlo – elegantly
19 2月, 2019
-
KX Product Insights: Insider Trading Alert
4 4月, 2019
-
KX Product Insights: Streaming ChartIQ in KX Dashboards
10 7月, 2019
-
How KX Surveillance helps detect benchmark manipulation in financial markets
22 8月, 2019
-
kdb+ and the History of the q Phrasebook
17 9月, 2019
-
Database Maintenance with q
19 10月, 2019
-
Kdb+ Version 4.0 – Faster, More Secure
23 3月, 2020
-
Python for Data Analysis… is it Really That Simple?!
2 4月, 2020
-
Visualizing Covid-19
8 4月, 2020
-
Dynamic Modeling of Covid-19
14 4月, 2020
-
Automated Machine Learning in kdb+
26 5月, 2020
Benchmarking KDB-X and KDB-X Python against Polars, DuckDB, ClickHouse, and Pandas
What the KX NYSE TAQ benchmark numbers actually say about memory need, query expressiveness and speed, and what we learned implementing 84 capital markets queries in six engines