Dev tools · alternatives · 2026
24 alternatives to HNSW index for vector embeddings in approx 500 LOC
Heirarchical Navigable Small Worlds. Contribute to dicroce/hnsw development by creating an account on GitHub.
This is a lightweight implementation of the HNSW (Hierarchical Navigable Small World) algorithm for indexing vector embeddings, written in approximately 500 lines of code. It is designed for developers who need fast… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
- 1
HNSW implementation in Rust. Reference: https://arxiv.org/ftp/arxiv/papers/1603/1603.09320.pdf - swapneel/hnsw-rust
2024 · github.com · its alternatives →
- 2
In an effort to understand it, I put together a simple, pure python implementation of HNSW, an approximate nearest neighbor library. Learned a lot, and I think for anyone interested in vector search it's an exercise that's absolutely worth doing. The code is optimized (imo) for readability, and working (albeit, quite slowly) on putting together a tutorial that walks through the motivation and implementation of HNSW. There's also working code examples for using the library for text and image search with sentence transformers and CLIP!
2025 · github.com · its alternatives →
- 3
Frustrated by the inability to play with semantic search / ANN in Go w/o a heavy-weight external DB, I created this HNSW library. I hope other gophers find it useful.
2024 · github.com · its alternatives →
- 4
End-to-end deep dive of the project, spanning a large GPU cluster, distributed RocksDB, and terabytes of sharded HNSW.
2025 · blog.wilsonl.in · its alternatives →
- 5
Accessible end-to-end deep dive of crawling, embedding, projecting, and semantic searching all of Hacker News for my Hackerverse project.
2024 · blog.wilsonl.in · its alternatives →
- 6MD
2023 · louisquissetlabs.com · its alternatives →
- 7IM
As a grad student (and an ADHDer), I had trouble doing literature review systematically. To combat this, I made a website that finds similar papers using the meaning of the thing I am looking for. I used MixedBread's [^1] embedding model to generate vectors from the abstracts. I store and search similar vectors using Milvus [^2] and finally use Gradio [^3] to serve the frontend. I update the vector database weekly by pulling the metadata dataset from Kaggle [^4]. To speed up the search process on my free oracle instance, I binarise the embeddings and use Hamming distance as a metric. I would…
2024 · papermatch.mitanshu.tech · its alternatives →
- 8
A high-performance observability data pipeline. Contribute to vectordotdev/vector development by creating an account on GitHub.
2019 · github.com · its alternatives →
- 9
Hey HN! I love finding new books to read on here. I wanted to gather the most mentioned books and recreate the serendipity of physical browsing. I scraped 20k comments from HN threads related to reading, extracted the references and opinions using GPT-4o mini, and visualised their embeddings as a map. - OpenAI's embeddings were processed using UMAP and HDBSCAN. A direct 2D projection from the text embeddings didn't yield visually interesting results. Instead, HDBSCAN is first applied on a high-dimensional projection. Those clusters tend to correspond to different genres. The genre…
2024 · hnbooks.pieterma.es · its alternatives →
- 10
Hello HN, I'm Ghita, co-founder of ZeroEntropy (YC W25). We build high accuracy search infrastructure for RAG and AI Agents. We just released two new state-of-the-art rerankers zerank-1, and zerank-1-small. One of them is fully open-source under Apache 2.0. We trained those models using a novel Elo score inspired pipeline which we describe in detail in the blog attached. In a nutshell, here is an outline of the training steps: * Collect soft preferences between pairs of documents using an ensemble of LLMs. * Fit an ELO-style rating system (Bradley-Terry) to turn pairwise comparisons into…
2025 · zeroentropy.dev · its alternatives →
- 11
Not all improvements come from adding complexity — sometimes it's about removing it. PageIndex takes a different approach to RAG. Instead of relying on vector databases or artificial chunking, it builds a hierarchical tree structure from documents and uses reasoning-based tree search to locate the most relevant sections. This mirrors how humans approach reading: navigating through sections and context rather than matching embeddings. As a result, the retrieval feels transparent, structured, and explainable. It moves RAG away from approximate "semantic vibes" and toward explicit reasoning…
2025 · github.com · its alternatives →
- 12CH
Hi HN! We're thrilled to share CozoDB v0.6, a monumental update to our FOSS database, which already unifies relational and graph features. With the addition of vector search, CozoDB becomes an even better companion for LLMs like ChatGPT. This release introduces vector search using HNSW indices within Datalog, enabling seamless integration with powerful features such as ad-hoc joins, recursive Datalog, and classical whole-graph algorithms. This update significantly broadens CozoDB's capabilities. Check out the linked release note for an in-depth look at the new features, comparisons to other…
2023 · docs.cozodb.org · its alternatives →
- 13AG
This is a vector index I built that supports insertion and k-nearest neighbors (k-NN) querying, optimized for GPUs. It operates entirely in CUDA and can process queries on half a billion vectors in under 200 milliseconds. The codebase is structured as a standalone library with an HTTP API for remote access. It’s intended for high-performance search tasks—think similarity search, AI model retrieval, or reinforcement learning replay buffers. The codebase is located at https://github.com/rodlaf/BinaryGPUIndex.
2025 · rlafuente.com · its alternatives →
- 14
I recently found myself computing the similarity between lots of very high dimensional vectors (i.e., sentence embedding vectors from LLMs), and I wanted to try some more powerful measures of similarity/dependency than just Cosine similarity, which seems to be the default for everything nowadays because of its computational efficiency. There are many other more involved measures that can detect more subtle relationships, but the problem is that some of them are quite slow to compute, especially if you're trying to do it in Python. For my favorite measure of statistical dependency,…
2023 · github.com · its alternatives →
- 15
We’ve just open-sourced Vicinity, a lightweight approximate nearest neighbors (ANN) search package that allows for fast experimentation and comparison of a larger number of well known algorithms. Main features: - Lightweight: the base package only uses Numpy - Unified interface: use any of the supported algorithms and backends with a single interface: HNSW, Annoy, FAISS, and many more algorithms and libraries are supported - Easy evaluation: evaluate the performance of your backend with a simple function to measure queries per second vs recall - Serialization: save and load your index for…
2024 · github.com · its alternatives →
- 16
Embedding Atlas▲150Hey HN, we're happy to release Mycelium, a JavaScript library for creating graph visualizations of machine learning models or any other directed acyclic graphs. Mycelium powers the graph viewer of the Talaria [0] a research model visualization and optimization system, which was used to optimize the efficiency of Apple Foundation Models [1]. Everything works entirely on the client-side in the browser — we provide a rudimentary ONNX loader out of the box, which you can try by dragging model files into our website. It is also simple to define loaders for your own model formats. The library was…
2025 · apple.github.io · its alternatives →
- 17AD
We (Nick, Dens, Denzell, Fede, Drew, Aaryan, and Daniel) have been building HN Discovery, a discovery-focused search engine for Hacker News, in our spare time for the past 6 months and are excited to show it! It adds the following features relative to the existing keyword search interface and preserves the existing ones: - no-JS version (hnnojs.trieve.ai) - site:{required_site} and site:{negated-site} filters - public analytics - LLM generated query suggestions based on random stories - recommendations - dense vector semantic search - SPLADE fulltext search - RAG AI chat - order by…
2024 · hn.trieve.ai · its alternatives →
- 18
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 · its alternatives →
- 19
Hey folks! As someone doing hybrid search daily and wishing I could have a pgvector-like experience but with actual prefiltered approximate nearest neighbours, I decided to just take a punt on implementing ACORN on a fork of the DuckDB VSS extension. I had to make some changes to (vendored) usearch that I'm thinking of submitting upstream. But this does the business. Approximate nearest neighbours with WHERE prefiltering. Edit: Just to clarify, this has been accepted into the community extensions repo. So you can use it like: ``` INSTALL hnsw_acorn FROM community; LOAD hnsw_acorn; ```
Mar 2026 · github.com · its alternatives →
- 20
Improved vector search with open-source AI embeddings editor
2023 · its alternatives →
- 21
Last week was insane for vector search. Weaviate raised $50M, and Pinecone raised $100M... That's a lot and makes you believe that vector search is hard. But it's not. I have spent the last couple of days implementing a single-file vector search engine from scratch, which is at least the tenth in the twenty years of my career. But this time, it's different. Instead of inventing a brand new algorithm and doing some crazy optimizations on the GPU, I: 1. took the standard HNSW algorithm, 2. fitted into 1000 lines of C++11 for portability, 3. added quantization and hardware-accelerated metrics,…
2023 · github.com · its alternatives →
- 22
The Virtual Feature Store. Turn your existing data infrastructure into a feature store. - featureform/featureform
2021 · github.com · its alternatives →
- 23
Hey HN, we're excited to show you client-vector-search, a client-side library that helps you embed, store, search, and cache vectors in your browser or node env. We needed it at https://searchbase.app and that's why we've built it. with it you get: 1. easy setup: you only need to add 5 lines of code to build a semantic search 2. no embedding api needed: you don't need an api and have to pay for it unless ure scaling up millions 3. faster search: modern hardware is better than cheap cloud computers (0.5vCPUs) 4. zero latency: no back-and-forth with server-side 5. easy integration…
2023 · clientvectorsearch.com · its alternatives →
- 24
A container for dataclasses with multi-indexing and bulk operations. - joshlk/dataclassframe
2020 · github.com · its alternatives →
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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 →