Dev tools · alternatives · 2026
24 alternatives to KMDS
KMDS is a library for data scientists and data analysts to capture knowledge and facilitate collaboration and reporoduciblity of data science tasks. Recipes for using KMDS with analytics and machine learning tasks are available at: https://github.com/rajivsam/kmds_recipes Please see the wiki section for documentation.
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. KMDS launched in 2024; newer entries below may have overtaken it.
- 1
Hey folks. I'm the author of kr8s. I’ve been working on kr8s for a while now and one of my core goals is to build a Python library for Kubernetes that is the most simple, readable and produces the most maintainable code. It should enable folks to write clean code when working with the Kubernetes API. If you're interested in how it compares with other libraries then check out [this post](https://jacobtomlinson.dev/posts/2023/comparison-of-kr8s-vs-...). Happy to answer any questions you might have in the comments here .
2023 · github.com · its alternatives →
- 2
Dataset Search▲345Making it easier to discover datasets. Made by Google.
2018 · datasetsearch.research.google.com · its alternatives →
- 3
- 4
Your home for data science and AI. The world's leading publication for data science, data analytics, data engineering, machine learning, and artificial intelligence professionals.
2019 · towardsdatascience.com · its alternatives →
- 5
Pandada AI▲620Build data wealth: Turns files into McKinsey-level insights
Jan 2026 · pandada.ai · its alternatives →
- 6
- 7DC
2016 · datasets.co · its alternatives →
- 8BA
2019 · bamboolib.com · its alternatives →
- 9PN
The source for financial, economic, and alternative datasets, serving investment professionals.
2013 · quandl.com · its alternatives →
- 10
- 11SP
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 · its alternatives →
- 12
Pandas is the most common python library for data analytics
2016 · amazon.com · its alternatives →
- 13
Know Your Data▲121Understand datasets & improve data quality, by Google PAIR
2021 · knowyourdata.withgoogle.com · its alternatives →
- 14
All-pair set similarity search on millions of sets in Python and on a laptop - GitHub - ekzhu/SetSimilaritySearch: All-pair set similarity search on millions of sets in Python and on a laptop
2018 · github.com · its alternatives →
- 15
A guide for anyone who works with data
2017 · leanpub.com · its alternatives →
- 16DA
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 · its alternatives →
- 17
The Open Source Data Science Masters. Contribute to datasciencemasters/go development by creating an account on GitHub.
2014 · github.com · its alternatives →
- 18
A container for dataclasses with multi-indexing and bulk operations. - joshlk/dataclassframe
2020 · github.com · its alternatives →
- 19
This little project came about because I kept running into the same problem: cleanly differentiating sensor data before doing analysis. There are a ton of ways to solve this problem, I've always personally been a fan of using kalman filters for the job as its easy to get the double whammy of resampling/upsampling to a fixed consistent rate and also smoothing/outlier rejection. I wrote a little numpy only bayesian filtering/smoothing library recently (https://github.com/hugohadfield/bayesfilter/) so this felt like a fun and very useful first thing to…
2024 · github.com · its alternatives →
- 20DD
Gleb, Alex, Erez and Simon here – we are building an open-source tool for comparing data within and across databases at any scale. The repo is at https://github.com/datafold/data-diff, and our home page is https://datafold.com/. As a company, Datafold builds tools for data engineers to automate the most tedious and error-prone tasks falling through the cracks of the modern data stack, such as data testing and lineage. We launched two years ago with a tool for regression-testing changes to ETL code…
2022 · its alternatives →
- 21
We've open-sourced Klarity - a tool for analyzing uncertainty and decision-making in LLM token generation. It provides structured insights into how models choose tokens and where they show uncertainty. What Klarity does: - Real-time analysis of model uncertainty during generation - Dual analysis combining log probabilities and semantic understanding - Structured JSON output with actionable insights - Fully self-hostable with customizable analysis models The tool works by analyzing each step of text generation and returns a structured JSON: - uncertainty_points: array of {step, entropy,…
2025 · github.com · its alternatives →
- 22
HyScale is an Application Centric Abstraction Framework over K8s. - hyscale/hyscale
2020 · github.com · its alternatives →
- 23
Hi HN, We're Anna, Adrian, Marcin and Matt, developers of dlt. dlt is an open source library to automatically create datasets out of messy, unstructured data sources. You can use the library to move data from about anywhere into most of well known SQL and vector stores, data lakes, storage buckets, or local engines like DuckDB. It automates many cumbersome data engineering tasks and can by handled by anyone who knows Python. Here’s our Github: https://github.com/dlt-hub/dlt Here’s our Colab demo:…
2023 · colab.research.google.com · its alternatives →
- 24
Also compare
Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →