Alternatives
Products that do what Dux, distributed DuckDB-backed dataframes on the Beam does
Hey all! I wrote Explorer[1] a good few years ago now with the dream of fast dataframes with a dplyr-like API in a really powerful, ergonomic language (Elixir). It's proved pretty successful. Explorer is used in production at my company, and it's my go-to for quick data analysis. But maintaining it became a true albatross. Polars is an amazing project, but the development process is fast and a lot is very focused on the Python lib. We found that trying to maintain Explorer against Polars was a maintenance nightmare and eventually hit points where we had to give up features and found it…
- 1VO
2018 · medium.com
- 2DI
2021 · github.com
- 3HP
I built this because I was tired of scrolling through hundreds of lines of AWS CLI JSON output just to find instance status. hawk brings pandas-like operations (select, group_by, aggregations) to CLI with unified syntax across JSON/YAML/CSV. Key features: - Instant data structure overview with `| info` - Same query syntax for all formats - Built in Rust for speed and single-binary distribution Would love feedback from the community!
2025 · github.com
- 4DR
We’ve built SQLRooms, an open-source framework for creating single-node data analytics apps powered by DuckDB. It lets you build fully client-side, data-centric apps using React and DuckDB running in the browser (via WebAssembly) or in Electron. No server or backend is required — apps can work offline, preserve data privacy, and run queries on large datasets with sub-second performance. Features: - Query large datasets in browser with DuckDB (WASM) - Modular design for building composable data UIs (query editors, dashboards, notebooks, etc.) - Data privacy-preserving AI assistant that can…
2025 · sqlrooms.org
- 5IM
2020 · github.com
- 6UI
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
- 7ME
Show HN: Mongo Explorer – Open-source AI-powered MongoDB management tool Mongo Explorer is an open-source project that integrates AI into MongoDB management, aiming to simplify database optimization and query generation. Key features include: 1. AI-assisted query generation: Convert natural language to MongoDB queries 2. Intelligent index suggestions with one-click creation 3. Visual query performance analysis and profiling 4. Schema exploration for collections and queries Tech stack: - Frontend: React - Backend: ASP.NET Core 8 - Deployment: Docker The AI integration uses OpenAI's GPT models…
2024 · github.com
- 8IB
I had 14,000 photos sitting on a drive and wanted an excuse to play with local vision models and Elixir/Phoenix. I originally tried to get LLaVA to tell me if a photo was 'good' or matched my style, but quickly learned that LLMs have terrible taste. I ended up demoting the LLM to just extract metadata, and built a custom CLIP/Ridge Regression pipeline to actually learn my preferences based on how I rate things. The stack is Phoenix/Oban on the orchestrator side, and Python/FastAPI/Instructor for the AI workers. Happy to answer any questions about the architecture,…
Apr 2026 · qwelian.com
- 9RS
Hey HN! We just released the open-source version of Renumics Spotlight, a data exploration and analysis tool for multimodal datasets. Spotlight integrates seamlessly with pandas and supports rich data types like images, videos, and meshes. You can load anything that fits in a DataFrame and view it through a customizable GUI featuring multiple interactive widgets: a data table, similarity map, histograms, scatter plots, and more. In the past, we have used Spotlight for exploratory data analysis and tackling various model and data-related problems in our machine learning projects. What are…
2023 · renumics.com
- 10DY
Hey HN! I'm open-sourcing DataKit today. GitHub: https://github.com/datakitpage/datakit Live demo: https://datakit.page DataKit is a browser-based data analysis platform that processes multi-gigabyte files (CSV, Parquet, JSON, Excel) entirely client-side using DuckDB-WASM. Your data never leaves your browser. What it does: • Process large files (tested up to 20GB) without any server • Full SQL interface powered by DuckDB compiled to WebAssembly • Python notebooks via Pyodide for data science workflows • Connect to remote sources (PostgreSQL, MotherDuck, S3) with…
Dec 2025 · github.com
- 11ST
Hey HN! I've been building CSV editors for 15 years. This is my third rewrite, and I think I finally got it right. Key features: - Excel-like operation for intuitive use - Equipped with basic to advanced tools necessary for handling CSV - Supports various formats and character encodings. Can handle CSVs with different column counts - Cross-platform (Windows/Mac, Linux coming soon) - Opens 100MB files in 1.6 seconds (12x faster than Excel) Tech stack: Tauri (Rust + React/TypeScript/TailwindCSS) Would love feedback from anyone dealing with large datasets daily! Website:…
2025 · smoothcsv.com
- 12DQ
What started as a Claude Code experiment turned into a browser-native SQL workbench I now use daily. Runs DuckDB WASM entirely in your browser. No backend, no installation, no signup. - Query local files (CSV, Parquet, Excel) – data never leaves your machine - Handles 100M+ rows, 50GB+ files in a browser tab - Full UI: Monaco editor, schema explorer, spreadsheet-style results grid - Share SQL via URL – anyone can run your query instantly - BigQuery connector built-in (Snowflake coming) v0.2 – actively developing. Feedback welcome. GitHub (MIT):…
Dec 2025 · sql.dbxlite.com
- 13ST
Hey HN community! Over the past year, AI copilots like Cursor and Windsurf have fueled a dramatic shift in software engineering workflows. And yet, many technical users in adjacent fields like data science and analytics have been unable to reap the rewards of this revolution. It turns out that the existing tools are a poor match for analytical workloads. Beyond that Cursor and similar tools have very poor support for Jupyter notebooks, data science is a fundamentally different discipline from software engineering and we believe it requires a correspondingly different tool. We're excited to…
Sep 2025 · sphinx.ai
- 14WM
Hi HN, I’ve spent the last decade building hardware products like humanoid robots, 3D printers, and self-driving tractors. I needed a tool to navigate technical documents faster, so I created one with friends. This tool helps with component search, cross-referencing, comparison, and debugging. We’d love your feedback, whether you find it useful or not. Thank you! Try it here: www.convergelab.ai
2024 · convergelab.ai
- 15PP
I’ve found that I don’t have any context about the data in my pipelines only know if the pipeline is successful or not. So I built panda-patrol which allows you to monitor each node in your DAG, use AI to generate data tests for your data, store data profiles, and more. All with this comes with dashboards and alerts. You can easily drop it into your Python-based data pipeline (i.e. Airflow, Dagster, Prefect, etc.) and just run your pipelines are you normally would — but with monitoring and more context. Hope its valuable to some people
2023 · panda-patrol.vercel.app
- 16OS
Existing OSS C++ projects like ClickHouse and DuckDB support reading from Iceberg tables. Writing requires Spark, PyIceberg, or managed services. In this PR https://github.com/timeplus-io/proton/pull/928, we are open-sourcing a C++ implementation of Iceberg integration. It's an MVP, focusing on REST catalog and S3 read/write(S3 table support coming soon). You can use Timeplus to continuously read data from MSK and stream writes to S3 in the Iceberg format. No JVM. No Python. Just a low-overhead, high-throughput C++ engine. Docker/K8s are optional. Demo…
2025 · github.com
- 17VA
2019 · towardsdatascience.com
- 18AB
Hey HN: Kaveh here, the founder of https://www.usage.ai/ We launched a new free tool to help engineers understand their AWS spend. Why? Because the way it's done now is a pain. DevOps and Software Engineers end up end up becoming cloud accountants or end up forking over a big % of their AWS bill for a tool to understand costs rather than focusing on business problems. Previous to founding Usage, I worked on high-performance computing research at JP Morgan Chase and as a software engineer at a number of smaller startups. Here's how this new tool works: It's fully self-serve and…
2022
- 19IB
I posted this a few weeks ago and the server died under the traffic. Fixed that by adding an in-mem caching layer with Redis/valkey and added CloudFront caching for static content. Also upgraded the server. Also fixed the Firefox bugs, trying again. It's a research tool for US stocks. Financials for ~10k companies pulled from SEC filings. You can chart any metric across companies, filter news by ticker, ask questions in plain English and get a chart back. There's also SQL console against the whole database, which is the part I like to use together with the AI chat (generates an SQL…
Jun 2026 · terminal.tesseractanalytics.ai
- 20IE
Hey HN, We built a library to interactively explore unstructured datasets directly from a dataframe: https://github.com/Renumics/spotlight Some background: We have worked on different ML solutions over the years, mainly in the industrial AI space. A crucial step for us is always to inspect and explore the data interactively with the team and the customer. This is true throughout the dev process: During EDA, model debugging, model comparison and monitoring. We have tried many different options for visualizing unstructured datasets in the past: Notebooks, dash apps, custom…
2023 · github.com
- 21IW
Input a SMILES string (or pick one molecule from the examples) and it returns up to 100k molecules closest in 3-D shape or electrostatic similarity – from 10+ billion scale databases — typically in under 5-10 s. *Why it might interest HN* * Entire index lives on disk — no GPU at query-time, less than ~10 GB RAM total. * Built from scratch (no FAISS index / Milvus / Pinecone). * Index-build cost: one Nvidia T4 (~ 300USD) for one 5.5B database. * Open to anyone, predict ADMET, export results as CSV/SDF. Full write-up & benchmarks (DUD-E, LIT-PCBA, SVS) in the pre-print:…
2025 · cheese-new.deepmedchem.com
- 22ES
Hi HN, I built EdgeVec, a vector database that runs entirely in the browser. It implements HNSW (Hierarchical Navigable Small World) graphs for approximate nearest neighbor search. Performance: - Sub-millisecond search at 100k vectors (768 dimensions, k=10) - 148 KB gzipped bundle - 3.6x memory reduction with scalar quantization Use cases: browser extensions with semantic search, local-first apps, privacy-preserving RAG. Technical: Written in Rust, compiled to WASM. Uses AVX2 SIMD on native, simd128 on WASM. IndexedDB for browser persistence. npm:…
Dec 2025 · github.com
- 23RA
2022 · github.com
- 24DN
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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