Dev tools · alternatives · 2026

24 alternatives to Tinyhnsw – The Littlest Vector Database

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!

Tinyhnsw is a pure Python implementation of HNSW (Hierarchical Navigable Small World), an approximate nearest neighbor search algorithm. Designed for developers wanting to understand vector search, it prioritizes… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.

1
A fast HNSW implementation in Rust▲111
HNSW implementation in Rust. Reference: https://arxiv.org/ftp/arxiv/papers/1603/1603.09320.pdf - swapneel/hnsw-rust
2024 · github.com · its alternatives →
2
HNSW index for vector embeddings in approx 500 LOC▲73
Heirarchical Navigable Small Worlds. Contribute to dicroce/hnsw development by creating an account on GitHub.
2025 · github.com · its alternatives →
3
Embeddable HNSW Library for Go▲11
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
Fast vector similarity using Rust and Python▲141
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 →
5CH
CozoDB, Hybrid Relational-Graph-Vector Database▲137
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 →
6
Vicinity – Fast, Lightweight Nearest Neighbors with Flexible Back Ends▲57
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 →
7
OctaneDB – Fast, Open-Source Vector Database for Python▲33
OctaneDB is an open-source vector database for Python that focuses on ultra-fast similarity search for high-dimensional data—perfect for AI/ML, semantic search, and large-scale document or embedding retrieval. What does it do? Store, index, and search millions of embeddings (text, images, etc.) with sub-millisecond query time. Supports in-memory and efficient HDF5 persistent storage. Integrates seamlessly with sentence-transformers for automatic text embedding. Key Features: 10x faster than Pinecone or ChromaDB for vector search and batch insertions. Advanced indexing: HNSW (approximate…
2025 · github.com · its alternatives →
8
HelixDB – Open-source vector-graph database for AI applications (Rust)▲237
Hey HN, we want to share HelixDB (https://github.com/HelixDB/helix-db/), a project a college friend and I are working on. It’s a new database that natively intertwines graph and vector types, without sacrificing performance. It’s written in Rust and our initial focus is on supporting RAG. Here’s a video runthrough: https://screen.studio/share/szgQu3yq. Why a hybrid? Vector databases are useful for similarity queries, while graph databases are useful for relationship queries. Each stores data in a way that’s best for its main type of query (e.g.…
2025 · github.com · its alternatives →
9
USearch – Smaller and Faster Single-File Vector Search Engine▲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 →
10
uFuzzy.js – A tiny, efficient fuzzy search that doesn't suck▲251
Hello HN! I became frustrated with the unpredictible/poor match quality and opaqueness of "relevance scores" in existing fuzzy and fulltext search libs, so I tried something different and this is the result. The main selling point is the result quality / ordering, with best-in-class memory overhead and excellent performance being bonuses. The API is pretty stable at this point, but looking for feedback before committing to 1.0. TL;DR The test corpus is a 4MB json file with 162k words/phrases, so give it a second for initial download. You can also drag/drop your own…
2022 · github.com · its alternatives →
11
DuckDB community extension for prefiltered HNSW using ACORN-1▲90
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 →
12
All-pair similarity search on millions of sets in Python and on laptop▲123
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 →
13
Pygooglenews – Python library for advanced Google News data mining▲165
If Google News had a Python library. Contribute to kotartemiy/pygooglenews development by creating an account on GitHub.
2020 · github.com · its alternatives →
14
Epsilla – Open-source vector database with low query latency▲111
Hey HN! We are building Epsilla (https://github.com/epsilla-cloud/vectordb), an open-source, self-hostable vector database for semantic similarity search that specializes in low query latency. When do we need a vector database? For example, GPT-3.5 has a 16k context window limit. If we want to let it answer a question about a 300 page book, we cannot put the whole book content into the context. We have to choose the sections of the book that are most relevant to the question. Vector database is specialized at ranking and picking the most relevant content from a large pool…
2023 · github.com · its alternatives →
15AD
A discovery-focused search engine for Hacker News▲193
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 →
16
TinyNPS▲175
Simple NPS feedback
2019 · its alternatives →
17AG
A GPU-accelerated binary vector index▲65
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 →
18
Embeddinghub: A vector database built for Machine Learning embeddings▲118
The Virtual Feature Store. Turn your existing data infrastructure into a feature store. - featureform/featureform
2021 · github.com · its alternatives →
19SF
Smart Fruit – A Python schema-based machine learning library▲44
I've made a small Python library, designed for quick-and-easy prototyping of machine learning models. It's built on top of scikit-learn, to serialize and deserialize data from the forms you're likely to have, to the format used in scikit-learn. https://github.com/madman-bob/Smart-Fruit It's pretty bare-bones at the moment, but I thought I'd see if there was any interest before spending too much time on it. Let me know what you think.
2018 · its alternatives →
20
Cherry2.0 – text classification without ML knowledge needed▲71
text classification - no machine learning knowledge needed - Windsooon/cherry
2019 · github.com · its alternatives →
21FS
Fashion Shopping with Nearest Neighbors▲76
I made this website with my wife in mind; it makes it possible to browse for similar fashion products over many different retailers at once. The backend is written in Swift, and is hosted on a single Mac Mini. It performs nearest neighbors on the GPU over ~3M product images. No vector DB, just pure matrix multiplications. Since we aren't just doing approximate nearest neighbors but rather sorting all results by distance, it's possible to show different "variety" levels by changing the stride over the sorted search results. Nearest neighbors are computed in a latent vector space. The model…
2025 · vibewall.shop · its alternatives →
22
BloomSearch – Keyword search with hierarchical Bloom filters▲66
Hey HN! I got nerd-sniped by Bloom Filters this weekend, specifically for searching datasets with high "cardinality" (number of unique items). They're an _amazing_ data structure that, at a fixed size, tracks potential set membership. That means unlike normal b-tree indexes, they don't grow with the number of unique items in the dataset. This makes them great for "needle in a haystack" search (logs, document) as implementations like VictoriaMetrics and Bing's BitFunnel show. I've used them in the past, but they've never been center-stage in my projects. I wanted high cardinality keyword…
2025 · github.com · its alternatives →
23
TF-IDF search engine in 30 lines of Scala▲43
Vector space model implemented in a few lines . Contribute to felipehummel/TinySearchEngine development by creating an account on GitHub.
2011 · github.com · its alternatives →
24
EdgeVec – Sub-millisecond vector search in the browser (Rust/WASM)▲7
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 →

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