Alternatives
Products that do what Orchest – Data Science Pipelines does
Hello Hacker News! We are Rick & Yannick from Orchest (https://www.orchest.io - https://github.com/orchest/orchest). We're building a visual pipeline tool for data scientists. The tool can be considered to be high-code because you write your own Python/R notebooks and scripts, but we manage the underlying infrastructure to make it 'just work™'. You can think of it as a simplified version of Kubeflow. We created Orchest to free data scientists from the tedious engineering related tasks of their job. Similar to how companies like Netflix, Uber and Booking.com…
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Dear HN, I am Riwaj, the cofounder of dstack.ai (https://github.com/dstackai). A few months ago, we built an online service that allows users to publish data visualizations from Python or R. The idea was to build a tool that did not require additional programming or front-end development for publishing data visualizations. Such a code can be invoked from either Jupyter notebook, RMarkdown, Python, or R scripts. Once the data is pushed, it can be accessed via a browser. Open-sourcing dstack: During our customer discovery phase, we realized that dstack.ai should integrate a lot…
2020
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Hi HN! I’m Alex from Parabola (https://parabola.io). Parabola is a visual programming tool for creating functional data flows that everyone can use. It’s entirely drag-and-drop, handles data sizes much larger than a traditional spreadsheet, calculates everything live, and can run your flows on a schedule of your choosing. I used to work in strategy consulting, doing data analytics for SMBs and Fortune 500 companies. The amount of time wasted on menial tasks was astounding. Things like cleaning data, generating custom reports, creating human workflows to solve shortcomings in third…
2018 · parabola.io
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Hi HN, Over the past 6 months I've been working on a technical book focused on helping aspiring data scientists to get hands-on experience with cloud computing environments using the Python ecosystem. The book is targeted at readers already familiar with libraries such as Pandas and scikit-learn that are looking to build out a portfolio of applied projects. To author the book, I used the Leanpub platform to provide drafts of the text as I completed each chapter. To typeset the book, I used the R bookdown package by Yihui Xie to translate my markdown into a PDF format. I also used Google docs…
2020
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Hi there Hacker News, I've started a side project http://datasourcehub.com which aims to be a platform for data scientists. The project is still in the idea phase so the UI/UX and functionality are all subject to change. Feel free to play around, below is a guest login, and make sure files are content type of 'text/csv'. All data is subject to deletion, it's just a sandbox right now! By reaching out to the Hacker News community I hope to reach expert data scientists and get their feedback. Below are some questions I'd like to answer and some proposed directions that this…
2013
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2019 · bamboolib.com
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2019 · github.com
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2019 · domino-clj.github.io
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2017 · gpestana.gitbooks.io
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Today you can easily adopt AI coding tools because you have git for branching and rolling back if AI writes bad code. We haven't seen this same capability for data and decided to build it ourselves. Nile is a new kind of data lake, purpose built for using with AI. It can act as your data engineer or data analyst creating new tables and rolling back bad changes in seconds. We support real versions for data, schema, and ETL. We'd love your feedback on any part of what we are building - https://getnile.ai/ What do you think?
Jan 2026
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Hi HN! I am an undergrad student trying to build interesting things with AI. Recently, I was looking for a dataset I could use for a new project. I realized that it is really frustrating to go through all the government websites (with terrible UX) just to find some usable dataset. I set out to build a GitHub for datasets, named DataHub. Right now, we have more than 1000 datasets from Montréal and New York City, with more cities coming soon (and possible government agencies). All of this is wrapped into a powerful search. It's a breeze to find a dataset to work on. I'd be interested to know…
2017
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Hi everyone, Anuj here, Dataherald CEO. There are a bunch of EXTERNAL data sources in the world that people use a lot -- think census data, Bureau of Labor Statistics (unemployment, inflation), but even proprietary data sources. I was tired of getting these into useable data pipelines every time I need need to use them. Dataherald simply creates data pipelines to hundreds of data sources and then lets you create auto-updating data viz -- all in under 60 seconds. The goal is to enable non-tech users to more easily use data, which has been a huge problem for me throughout my career. We…
2022 · medium.com
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2020 · medium.com
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As a software engineer, it's frustrating to see those who can't code stuck with spreadsheets as their most powerful data tool. This is especially true when there is such a thin layer that exists to access arbitrarily powerful data and AI/ML tools (typically just Python and pandas/SQL). I built Regrail last year to demonstrate a visual, procedural tool that abstracts the primitives of data engineering. It uses a block-based editor that allows users to see the changes they are making to tables step by step. You can think of it like a visual DAG builder. I believe that data literacy…
2023 · regrail.io
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Hey everyone! I am excited to share updates on four of my & my teams' open-source projects that take large-scale search systems to the next level: USearch, UForm, UCall, and StringZilla. These projects are designed to work seamlessly together, end-to-end—covering everything from indexing and AI to storage and networking. And yeah, they're optimized for x86 AVX2/512 and Arm NEON/SVE hardware. USearch [1]: Think of it as Meta FAISS on steroids. It's now quicker, supports clustering of any granularity, and offers multi-index lookups. Plus, it's got more native bindings than probably…
2023 · usearch-images.com
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2016 · github.com
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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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