39 posts tagged with "kdb/q"

Not Only the Weather Is Heating Up…​

Not only have the temperatures been rising this summer, but so has the market for exciting new projects in the k and q ecosystem. While I'm aware of several groups quietly working on some very interesting ideas behind the scenes, L-Labs a new entity founded by K/Q veteran and former HFT engineer Jacob Loveless, is the first to bring something new to market.

Meet L.

A brand-new runtime for k and q that has just become publicly available, with the ambitious goal of rethinking how k and q applications are executed.

As someone who spends a large amount of time looking at everything happening around the KDB/Q ecosystem, it's always exciting to see innovation emerge, especially when it comes from someone who has been working with the language for years.

A few months ago, I wrote a blog post about Nasdaq's plans to extend trading hours and what that might mean for market data infrastructure. At the time, the discussion was largely theoretical. It was easy to dismiss it as yet another market structure change that would slowly work its way through committees, working groups, and technology roadmaps.

The more I thought about it, however, the more I realised that extended trading hours are not really about trading hours at all.

They are about a much bigger shift taking place across financial markets.

Markets are becoming more continuous. More fragmented. More data-intensive. More demanding.

And most importantly, they are beginning to expose assumptions that have been baked into market data systems for decades.

That's exactly why I'm excited to be joining KX for an upcoming webinar discussing the infrastructure implications of always-on markets. Together we'll explore what extended trading hours, odd lots, sub-penny pricing, AI-driven workflows, and increasingly continuous markets mean for firms operating in today's landscape.

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.

Let’s be honest: learning KDB/Q can sometimes feel like going to the gym. You know it’s good for you. You know you should keep practicing. But after a long day of debugging code, fighting with type errors, and wondering why your function suddenly returned a rank error, the last thing you want is to sit down and read another page of documentation.

That’s exactly why we’re launching the DefconQ Weekly KDB/Q Challenge.

The idea is simple: have a bit of fun, keep your Q brain sharp, and improve your KDB/Q skills on the side, without it feeling like homework. Every week, a new KDB/Q challenge will be posted on the DefconQ Community Discord Server, and everyone is invited to participate.

The DefconQ Community Server is officially live. Over the last few years, DefconQ has grown from a simple technical blog into something much bigger: a growing community of KDB/Q developers, engineers, quants, and vector programming enthusiasts who genuinely care about learning, building, and pushing the ecosystem forward. Launching a dedicated community server felt like the natural next step.

If you’ve been around the KDB/Q ecosystem for a while, chances are you’ve come across the legendary Iverson College. Founded by former KX Librarian Stephen Taylor in honour of Kenneth E. Iverson, the inventor of APL, the college has been running since 2011. After a brief hiatus between 2018 and 2023, it made a strong return in 2024. This year DefconQ joins forces with Stephen to reconvene the College at one of its favourite venues: Milden Hall.

The DefconQ Events are back, and this time, we’re taking over The Globe. Well...the Globe at Moorgate.

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.

As promised, I’m hosting a Reddit AMA (Ask Me Anything) on November 13th, 2025, where I will be answering all your questions about KDB/Q, the world’s most powerful time-series database and array programming language.

Over the years, I’ve received countless messages about:

• 💡 How to start learning KDB/Q
• 🚀 Career paths and progression in the KDB/Q ecosystem
• 📚 Best learning resources and study plans
• ⚙️ Real-world applications and architecture insights

So instead of replying to everyone one by one, let’s bring it all together. The AMA will run for 24 hours, and you will be able to ask your questions completely anonymously.

Looking forward to hearing from you all!

DefconQ

You can find the link here: Reddit DefconQ AMA

Last week marked one of my professional highlights of the year, the long-awaited Quant Strats conference finally took place! Hosted on October 14–15 at Convene 22 Bishopsgate in London, the event delivered two action-packed days filled with cutting-edge insights, technical deep dives, and forward-thinking discussions at the intersection of quantitative finance, AI, and data infrastructure. Just like last year, this blog post will recap the event and share some of the key highlights. Among them was undoubtedly my KDB/Q Masterclass, a deep dive into Wall Street’s most powerful array programming language and real-time database. Keep reading to find out more.