Alternatives
Products that do what Magniv, One line data science infra does
Hey HN! We are https://www.magniv.app/ - Magniv is a platform to enable data scientists to autonomously create, deploy, and maintain data applications within existing infra pipelines. That is, reduce data science reliance on data engineers in mature data organizations. While living between both worlds of software engineering and data science, we have seen a lack of mature organizational tooling for data scientists. Data teams either require embedded data engineers or companies are forced to find a unicorn full-stack data software engineer to hire. On top of that, the tooling…
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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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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
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2022 · mage.ai
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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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2022 · opendatadiscovery.org
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Hey HN! Mike & Warren here from HyperDX (now part of ClickHouse)! We’ve been building ClickStack, an open source observability stack that helps you collect, centralize, search/viz/alert on your telemetry (logs, metrics, traces) in just a few minutes - all powered by ClickHouse (Apache2) for storage, HyperDX (MIT) for visualization and OpenTelemetry (Apache2) for ingestion. You can check out the quick start for spinning things up in the repo here: https://github.com/hyperdxio/hyperdx ClickStack makes it really easy to instrument your application so you can go…
2025 · github.com
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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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Hello HN. I've always found writing data visualisation scripts boring and repetitive in data science workflows earlier in my career, so I built this tool to automate it. The available methods are based on my experience in econometrics where histograms and scatterplots were the starting points to check data distributions. The link is to the documentation and the app is freely available at https://visprex.com, and if you're curious about the implementation it's open source at https://github.com/visprex/visprex. I'd appreciate any comments and feedback!
2024 · docs.visprex.com
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