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Products that do what Skyulf does

Own your ml pipeline

  1. 1
    Skyulf6

    Own Your Machine Learning Pipeline Locally

    Dec 2025 · skyulf.com

  2. 2TA

    I built a SQLite VFS in Rust that serves cold queries directly from S3 with sub-second performance, and often much faster. It’s called turbolite. It is experimental, buggy, and may corrupt data. I would not trust it with anything important yet. I wanted to explore whether object storage has gotten fast enough to support embedded databases over cloud storage. Filesystems reward tiny random reads and in-place mutation. S3 rewards fewer requests, bigger transfers, immutable objects, and aggressively parallel operations where bandwidth is often the real constraint. This was explicitly inspired…

    Mar 2026 · github.com

  3. 3

    Build serverless APIs in minutes

    2024

  4. 4
    Porter415

    Heroku that runs in your own cloud

    2021

  5. 5
    Sparrow457

    The lightest and fastest platform for API testing

    2025

  6. 6OS

    I've been working on this for some time now, starting with vm2, then deno-core for 2 years, and recently rewrote it on rusty_v8 with Claude's help. OpenWorkers lets you run untrusted JS in V8 isolates on your own infrastructure. Same DX as Cloudflare Workers, no vendor lock-in. What works today: fetch, KV, Postgres bindings, S3/R2, cron scheduling, crypto.subtle. Self-hosting is a single docker-compose file + Postgres. Would love feedback on the architecture and what feature you'd want next.

    Jan 2026 · openworkers.com

  7. 7PC

    Hi HN! Porter Cloud (https://porter.run/porter-cloud) is a Platform as a Service (PaaS) like Heroku, but we make it easy for you to migrate to AWS, Azure, or GCP when you're ready. Like Heroku, Porter takes care of a lot of generic DevOps work for you (like setting up CI/CD, containerizing your applications, autoscaling, SSL certificates, setting up a reverse proxy) and lets you deploy your apps with a few clicks — saving you a lot of time while developing. However, as you probably know, there’s a downside: platforms like this become constraining if and when your app…

    2024

  8. 8HF
  9. 9

    Heroku that runs in your own cloud (AWS/GCP/DO)

    2021

  10. 10

    On-demand virtual warehouse to run ad hoc queries in 30 secs

    2024

  11. 11

    Managed RAG pipelines, made easy

    2025

  12. 12
    Morph 1.0320

    AI-powered BI dashboard across your SaaS data

    2023

  13. 13IB

    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

  14. 14AB

    I created a web page to compare different analytical databases (both self-managed and services, open-source and proprietary) on a realistic dataset. It contains 20+ databases, each with installation and data loading scripts. And they can be compared to each other on a set of 43 queries, by data load time or by storage size. There are switches to select different types of databases for comparison - for example, only MySQL compatible or PostgreSQL compatible. If you play with the switches, many interesting details will be uncovered. Full description:…

    2022 · benchmark.clickhouse.com

  15. 15SA

    Hi HN, We're Luke and Phillip, and we're building Spice.ai OSS - a lightweight, portable runtime, built in Rust and powered by Apache DataFusion to locally materialize, accelerate, and query data tables sourced from any database, data warehouse or data lake. Phillip and I first introduced Spice on Show HN in September 2021. Since then, we’ve been schooled and humbled in every way building 100TB+ data and ML systems for the https://spice.ai cloud platform. Along with our customers, we struggled with getting fast, low-latency, high-concurrency SQL query within a budget, accessing and…

    2024 · github.com

  16. 16BB

    Hi HN, Three months ago, I took a job at Baseten to help craft and document an application builder that lets data scientists build full-stack, production-ready applications around their ML models without worrying about containers, Flask, or React. From my first day, everyone was focused on what would happen today: opening up our public beta. I’m super excited to see what you build with Baseten. If you want to take Baseten for a full-speed test drive, follow along with this tutorial, where you can build and deploy an application in 20 minutes:…

    2022 · baseten.co

  17. 17
    UnionML77

    The easiest way to build and deploy ML microservices

    2022

  18. 18
    IOpipe107

    Application operations platform for serverless

    2017

  19. 19AA

    Atlas is an open-source deployment pipeline platform built for cloud-native applications. Atlas allows users to: - Create continuous pipelines across all their environments and clusters - Add custom tasks/tests plugins (Python scripts, K8S manifests, Argo Workflows, environment setup, etc.) - Automatically rollback applications in case of failure or degradation (Atlas watches the application past the scope of a pipeline run to ensure and enforce stability) - Use all existing Argo features Would love to hear all of your feedback and thoughts on this!

    2022 · greenops.io

  20. 20SA
  21. 21
    Hoplite154

    Effortlessly deploy cloud software factories.

    24d ago · hoplite.sh

  22. 22

    Open source SQL interface to your favorite cloud APIs🧑‍💻

    2022

  23. 23VS

    Hey HN! We’re Emma and Chris, founders of Velvet (https://www.usevelvet.com). Velvet proxies OpenAI calls and stores the requests and responses in your PostgreSQL database. That way, you can analyze logs with SQL (instead of a clunky UI). You can also set headers to add caching and metadata (for analysis). Backstory: We started by building some more general AI data tools (like a text-to-SQL editor). We were frustrated by the lack of basic LLM infrastructure, so ended up pivoting to focus on the tooling we wanted. So many existing apps, like Helicone, were hard to use as power…

    2024 · usevelvet.com

  24. 24

    The fastest way to build your data warehouse

    2023

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