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Products that do what A new language for COBOL workloads, built on Go does
We’re building an open-source language layer on top of Go, designed specifically for COBOL-style workloads: Native decimal arithmetic (COBOL-accurate) Record structures and copybook compatibility Batch jobs and transactional orchestration as first-class constructs Sequential / indexed file I/O baked into the runtime Compiles through Go for speed, concurrency, and cloud deployability Think of it as Kotlin for COBOL, or “COBOL on Go” familiar to mainframe engineers, powerful for modern developers. Test Results so far: NIST COBOL-85 validation: 77.61% overall (305/393 tests) NC…
- 1IB
Every data pipeline job I had to tackle required quite a few components to set up: - One tool to ingest data - Another one to transform it - If you wanted to run Python, set up an orchestrator - If you need to check the data, a data quality tool Let alone this being hard to set up and taking time, it is also pretty high-maintenance. I had to do a lot of infra work, and while this being billable hours for me I didn’t enjoy the work at all. For some parts of it, there were nice solutions like dbt, but in the end for an end-to-end workflow, it didn’t work. That’s why I decided to build an…
2024 · github.com
- 2IM
Let-go is a Clojure-like language (~90% compatible with JVM Clojure) written in pure Go. It ships as a ~10MB static binary and cold boots in ~7ms - that's about 50x faster than JVM and 3x faster than Babashka. It has decent throughput on algorithmic workloads - within ballpark of the GraalVM-backed sci. I started this project in 2021 as an elaborate practical joke: I wanted to have an excuse for writing Clojure while pretending to write Go. Jokes aside, it turned out to be pretty decent: it feels like real Clojure, it has an nREPL server (supported in Calva, CIDER, etc.), it's easily…
May 2026 · github.com
- 3CR
This is an evolving toolkit of capabilities helpful for analysing and reverse engineering legacy Cobol code. Currently, the following capabilities are available: - Program / Section-level flowchart generation based on AST (SVG or PNG) - Parse Tree generation (with export to JSON) - Control Flow Tree generation (with export to JSON) - Allows embedding code comments as comment nodes in the graph - The SMOJOL Interpreter (WIP) - Injecting AST and Control Flow into Neo4J - Injecting Cobol data layouts from Data Division into Neo4J (with dependencies like MOVE, COMPUTE, etc.) + export to…
2024 · github.com
- 4MM
I've been working on implementing the compile-time approach to memory management described in this thesis (https://www.cl.cam.ac.uk/techreports/UCAM-CL-TR-908.pdf) for some time now - some of the performance results look promising! (Although some less so...) I think it would be great to see this taken further and built into a more complete functional language.
2020 · github.com
- 5CA
Hello Hacker News. I’m Martin, a graduate student from Prague, and I’ve been working on Coros, a C++ library for task-based parallelism. After spending some time with OpenMP and oneTBB, I wanted to try building a library using modern features from the C++ standard library. I’ve used coroutines for task encapsulation and C++23 expected for exception handling, while trying to maintain good performance. Additionally, I’ve implemented monadic-like behavior to allow easy chaining of tasks, similar to the monadic operations in std::expected. You can check out the project here:…
2024 · github.com
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Mar 2026 · github.com
- 7GA
We built Gonzo to make log analysis faster and friendlier in the terminal. Think of it like k9s for logs — a TUI that can ingest JSON, text, or OpenTelemetry (OTLP) logs, highlight and boil up patterns, and even run AI models locally or via API to summarize logs. We’re still iterating, so ideas and contributions are welcome!
2025 · github.com
- 8UD
Hey HN! I’m the founder of Unify, and we’ve just released our Model Hub, which provides a collection of LLM endpoints with live runtime benchmarks all plotted across time: https://unify.ai/hub A key finding is that static tabular runtime benchmarks for LLMs simply do not work. It’s necessary to take a time-series perspective, and plot the variations through time. We currently have 21 models provided by: Anyscale, Perplexity AI, Replicate, Together AI, OctoAI, Mistral AI and OpenAI, with more on the roadmap. We test across different regions (Asia, US, Europe), with varied…
2024
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2020 · github.com
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I'd like to share a project I've been working on for the past few months. It's a distributed workflow engine written entirely in Go. Some highlights: * Tasks are executed in a Docker container * Can run stand-alone or distributed * Highly extensible * Able to enforce limits (CPU/RAM) per task * Web UI Would love the get your feedback on it, and find out if this could be useful.
2023 · github.com
- 15WA
tiny_coro is a lightweight, educational M:N asynchronous runtime written from scratch using C++20 coroutines. It's designed to strip away the complexity of industrial libraries (like Seastar or Folly) to show the core mechanics clearly. Key Technical Features: M:N Scheduling: Maps M coroutines to N kernel threads (Work-Stealing via Chase-Lev deque). Memory Safety: Implements EBR (Epoch-Based Reclamation) to manage memory safely in lock-free structures without GC. Visualizations: I used Manim (the engine behind 3Blue1Brown) to create animations showing exactly how tasks are stolen and…
Feb 2026 · github.com
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High performance storage engine for efficient LLM inference and GPU Training.
18h ago · theopenlake.com
- 17CL
Hey HN, we’re the developers of OpenLake, an open source storage engine for offloading LLM KV caches from GPU memory into a shared tier of RAM and NVMe. We built OpenLake because KV caches are outgrowing GPU memory. A single 256K token conversation on Gemma 4 31B produces approximately 43GB of KV state, more than half the memory of an 80GB H100. The problem becomes even harder across a cluster: a prefix cached on one GPU host is unavailable when the next request lands on a different GPU, forcing the new GPU to repeat work the fleet has already completed. Once the KV cache is offloaded,…
Jul 2026 · github.com
- 18SA
Hi HN! I’m Tony, one of the co-founders of Inngest (https://inngest.com/). Wanted to show you something we’re working on: StepKit. StepKit is an open source SDK and framework for building and iterating on durable workflows that run on any platform (self-hosted, Inngest, Cloudflare, Netlify, etc.) without requiring any provider or bundler-specific code. Here’s the repo: https://github.com/inngest/stepkit. StepKit extracts the core execution loop that we built in Inngest and makes it fully open, Apache 2, and hackable/pluggable to different backends. We…
Nov 2025
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2014 · team.s4y.us
- 20GA
I started working on this back in 2019, mostly as a design idea. Over the last month I made a big push to make it 100% usable and replace C# in all my personal projects. I now feel it's solid enough to gather feedback from other developers. If you take it for a spin, I hope you enjoy it and send your thoughts!
Jun 2026 · davidobando.github.io
- 21AI
Hi HN, I’m Sean, the founder of Ascend.io (https://www.ascend.io). I’m really excited to post here and announce the launch of Ascend.io, a radical new way of designing, scaling, and automating data pipelines. Ascend is the result of nearly 4 years of development effort for a team that is now 30-strong, and I would love for you to give it a test drive and let me what you think. I’ve felt this pain since I wrote my first MapReduce in 2004 (using Sawzall @ Google), and in the 15 years since, things have not improved at the pace of other parts of the technology ecosystem. When I went…
2019
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2017 · github.com
- 23BH
Hello HN, I’m excited to share Bodo, an open-source compute engine designed for large-scale data processing in native Python. Bodo is powered by an auto-parallelizing JIT compiler and an HPC backend, enabling it to generate highly optimized, parallel binaries (MPI) for Pandas and NumPy code—all without requiring any code rewrites. Our latest benchmark demonstrates 20x to 240x speedup over traditional distributed computing frameworks like Spark, Ray, and Dask (code and details in repo). The inspiration for Bodo came from my background in HPC, when I saw how extremely slow and hard to use…
2024 · github.com
- 24SA
2012 · github.com
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