2 posts tagged with "Big Data"

There Is No KDB Without Market Data​

Let’s be honest: there is no KDB/Q without market data.

You can build the cleanest tickerplant in the world, design elegant schemas, optimise queries until they scream, and architect the perfect stack, but without data flowing into it, it’s all just a very expensive and slightly nerdy sculpture.

Market data is the lifeblood of every serious KDB/Q system. It’s where the story begins. And yet, for something so fundamental, getting access to market data as an individual developer has historically been ... painful.

That’s exactly why I’m excited to announce that DefconQ and Databento are teaming up for an upcoming Meetup in London, a community event for quants, financial engineers, developers, and anyone working with market data who wants to see what happens when market data stops being a headache and starts becoming something you can actually work with.

Yesterday (2025.12.16) Nasdaq announced an extension of its trading hours, a move that once again reshapes how modern markets operate. While headlines focus on increased accessibility and global participation, the real impact is felt much deeper in the technology stacks that power trading, analytics, and risk systems. Extending trading hours is not just a business or regulatory change. It’s a data engineering problem. And a non-trivial one. In this post, I want to unpack what extended trading hours actually mean from a technical perspective, why many traditional data architectures will struggle, and why systems built with KDB/Q (or KDB-X) are particularly well suited to absorb this change without breaking a sweat.