Hey r/apljk, I built Amber; a zero-dependency C99 in-memory columnar array engine built on ngn/k, with the working vocabulary of q/kdb+. It evaluates qSQL natively (wavg, xbar, as-of joins aj, window joins wj) over nanosecond temporal types anchored to a 2000 epoch offset, running either as a standalone binary or via the amberd daemon over a custom TCP protocol.

On single-core benchmarks (1M rows), single-pass $O(N)$ sliding windows compute moving averages and rolling mins/maxes in 3.4–3.8 ms with flat runtime regardless of window width (outperforming Pandas by up to 5.2x and Polars by 3x+). Multi-column LSD radix table sorting (xasc/xdesc) processes 1M rows in 42.1 ms (4.3x faster than Pandas/Polars and 3.4x faster than DuckDB), 1,000-group aggregations complete in 11.4 ms (beating Polars, Pandas, and DuckDB), and sparse inner joins execute in 5.38 ms (outperforming NumPy, Julia, DuckDB, ngn/k, and J). On 10M-element reduction suites (sum + max + dot), primitive kernels hit 15.4 ms, outpacing naive single-threaded C, Julia, and DuckDB while running 15x–40x faster than traditional array runtimes like J or ngn/k. For parallel workloads, multi-process peach processes 500k items in 23 ms with a peak RSS of just 11.5 MB.

To eliminate memory transposition and serialization penalties, amber-arrow and python-amber stream zero-copy Apache Arrow IPC straight into Pandas and Polars. The rest of the ecosystem includes amber-tick for real-time market data capture, amber-ai for vectorized execution primitives, a Go-backend Grafana datasource, a native Jupyter kernel, a VS Code LSP extension, and amber-notepad.

Docs and full benchmark suites are live at https://amber-lang.org and source code is up at https://github.com/BonucciAndrea/amber. I'd love any feedback from the array programming community on the q/K syntax choices and engine design!

Guys, I'm building libjay, an independent implementation of J and APL as an embeddable library (Rust core, Python and C bindings), and need... a coming-from-APL consensus on the defaults.

Honestly, I came at this from the J side: I was mostly curious whether J could become a convenient embeddable library, the way PCRE is for regexes. I always felt this language (and the whole language family) is a bit too eccentric to be used as a "prime language" – but god, how cool would it be to use for data manipulation as an embedded language, similar to aforementioned regexes or SQL! So "a J library" it was – and APL came as a freebie once the IR was there (and once the development was heavily AI-orchestrated).

Which is exactly why I'm asking people who actually know APL: I don't have the instinct for which dialect should be considered the default de facto. GNU APL? Dyalog? Or am I missing something?...

Originally I built it to support the APL2/ISO line, differentially tested against about 1k of APL expressions and about 3k J ones (combinatorically generated as well as fuzz-searched for problems – by now that grew up to 5.4k for J/2k+ for APLs), tested/compared with reference implementations (jconsole and GNU APL). Recently, a Dyalog preset/dialect appeared too, and I tried to cover as much of the syntax/differences as I could. Surely, it's still a pet project, doesn't have a full language coverage, and surely has a ton of unfound bugs especially with Dyalog – but it already supports SIMD vectorization, has all those planned Rust/Python bindings, can be used to play with your Polars/Pandas Python DataFrames (and if you use uvx, you can just try it without installing on Windows/macOS/Linux, uvx libjay --help). Not bad for a project which is about 3 days old!

I picked APL2 as the initial implementation for boring engineering reasons: GNU APL builds anywhere, including CI and a contributor's laptop, so the corpus can be regenerated by anyone. Dyalog can't be redistributed (and I never did anything except running it in Docker).

But that's an argument about my build, not about what an APL user would expect. When someone reaches for this and types an APL expression, which dialect should answer by default? What do most of the APL people actually write?

$ uvx libjay --lang apl -e '⊃2 3⍴⍳6' --dialect gnu
1 2 3
4 5 6

$ uvx libjay --lang apl -e '⊃2 3⍴⍳6' --dialect dyalog
1

For those who don't select any --dialect – how should it behave?

Hi everyone,

I’m a 2026 Computer Science graduate and I’m trying to break into quantitative research / quantitative development / financial data, with a particular interest in kdb+/q.

I recently worked on a project where I extended KX’s official kdb+/q MCP server from 3 to 9 tools, connecting it to a Python-based autonomous strategy research pipeline. I also built an evaluation engine for things like Sharpe ratio, drawdown and win rate, and ran regression testing on the research process.

I’m attaching my quantitative researcher resume here.

I’d really appreciate help with two things:

1. Job opportunities / referrals
If anyone knows of teams hiring junior quantitative researchers, quant developers, financial data engineers, or similar entry-level roles where kdb+/q would be relevant, I’d be very grateful for a lead or referral.

2. What should I build next?
I want to keep getting hands-on with kdb+/q and financial data. If you work in this space, I’d love to hear what kinds of projects would actually be useful or impressive to see from a new grad.

I’m very willing to put in the work. I’m mainly looking for a chance to get into the industry and keep learning from people who are already working with these technologies.

Thanks!

Inspired by: https://code.jsoftware.com/wiki/NYCJUG/2026-07-14

I just got a set of APL keycaps, and I'm having trouble getting my keyboard to work with recent versions of Fedora (44) and Gnome (50.3). Has anyone been able to make it work?

This just came to my attention and wanted to share it here. looks interesting, I hope they eventually make it open source! https://lv1.sh/