[clausok]

Kx released a 32bit, free-for-commercial-use version in 2014 and then reversed course around a year later after banks and hedge funds surprised them by flocking to it for a large subset of their developers / dev machines.

Hopefully they stick to it this time around. It's an incredible system. It's the only thing I've ever used, including Pandas, dplyr & Matlab, where someone could stand over my shoulder asking data analysis questions and I could answer them, on the fly.

LLM's, though notoriously bad (so far) at KDB+/Q compared to other languages, are still a godsend for folks getting started. I recently returned to writing Q after being away from it for 8 years and I've been amazed how good even Google's AI suggestions have been at helping with functions & queries.

Getting started tip: try using Q strictly as a query language, avoid K. Do everything else (data shoveling, devops,...) with a different language.

[0cf8612b2e1e]

Could you give an example of where it shines? I have had to answer many a SQL/pandas question with someone over my shoulder, so curious where you see the sharpest benefit.

Admittedly, I am unlikely to learn this proprietary DSL, but always good to know what is the best tool for a job.

[AUnterrainer]

Q is not just a query language or a database. It's an array programming language with database capability. You can build an entire framework with just Q, from real-time streaming, to in memory database to on disk database. You can build all APIs and business logic around it. Because it's vector oriented and in memory it's faster than pretty much everything else, no loops required. I have seen a team of 15 KDB developers build what would require an entire etrading department of 200+ developers

[leprechaun1066]

Given Wes McKinney created Pandas for quantitative analysis, it's possible that Pandas wouldn't exist if AQR were paying for a q license.