Alternatives
Products that do what EdgeVec – Sub-millisecond vector search in the browser (Rust/WASM) does
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:…
- 1SA
2019 · github.com
- 2HC
2021 · github.com
- 3
- 4
- 5ZT
Zvec is a lightweight, SQLite-like embedded vector database purpose-built for edge and on-device workloads. It delivers four core advantages: out-of-the-box usability, configurable resource budgets, extreme performance, and versatile vector capabilities. Open-sourced under the Apache 2.0 license, Zvec aims to provide developers with a one-stop path from prototyping to production deployment on the edge. Try Zvec—we’re excited to see your adoption, feedback, and contributions. For a more detailed introduction, you can refer to https://zvec.org/en/blog/introduction/
Jan 2026 · github.com
- 6VW
2020 · github.com
- 7PV
Search a 100,000-article ParqDB index directly in the browser with MiniLM, HTTP Range, Parquet, and WebAssembly.
16d ago · search.parqdb.io
- 8SV
Hi HN, I'm Daniel from Superlinked! We have built an open-source framework that improves vector search relevance and usefulness by combining structured metadata with unstructured data in your embeddings. We included self-hostable API server that sits between your data sources and vector database. Docs: https://docs.superlinked.com/ We're launching our cloud offering soon where you can use Superlinked to orchestrate high-performance retrieval for RAG, Search & Recommendation apps in your own cloud. Looking for feedback and happy to answer questions!
2024 · github.com
- 9IW
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
- 10TA
In this post, we document the results of some experiments comparing vanilla Graph RAG (just a single pass of text2cypher) vs. a router agent Graph RAG approach that can call vector search tools alongside text2cypher. The routing agent uses an LLM to decide which vector search tool to call, depending on the terms identified in the question, and it works quite well. The results show that recent frontier LLMs like `gpt-4.1` and the trusty workhorse `gemini-2.0-flash` produce great quality Cypher reliably and reproducibly, with some prompt engineering to ensure that the graph schema is formatted…
2025 · blog.kuzudb.com
- 11LS
MyScale is designed for the storage and analysis of massive vector data with structured metadata. If you are eager to find a high-performance vector search using SQL queries, MyScale could be your preferred option. Thanks to the advantages of native structural database support, it provides you with a flexible filter with a WHERE clause, even JOIN when you want to jointly search vectors with filters on relevant metadata from other tables. MyScale is now open for registration and offers millions of vectors‘ free tier plan for you! (https://myscale.com/) Now you can also use…
2023 · myscale.com
- 12DR
2018 · dropbox.github.io
- 13
I've been working on Polign and built a small prototype around something I've been thinking about with agent memory. I have built a lightweight/stateless vector db + BM25 search which works really well with typed facts and structured queries. It uses your own S3, or GCS bucket as primary storage, and restarting a node is fairly quick. Demo + writeup: https://polign.com/blog-edge-agent-memory Live search demo: https://demo.polign.com Docs: https://polign.com
11d ago · polign.com
- 14T5
2021 · tensorbase.io
- 15SQ
Dec 2025 · github.com
- 16ZP
Hey HN - we launched Zep's document vector DB today. Zep is an open source memory store for LLM apps, and this builds on existing chat history memory persistence, embedding, and enrichment capabilities. Zep uses Postgres and pgvector for database operations and vector search. Vector search can be complicated on Postgres, with careful configuration required at both index creation and query time. We've focused on significantly improving this developer experience. Zep automatically selects index and query parameters for developers based on best practices and known heuristics. Vector database…
2023 · github.com
- 17SS
I built https://ask.rivestack.io — a semantic search engine over Hacker News posts. Instead of keyword matching, it finds results by meaning, so you can search things like "best way to handle authentication in microservices" and get relevant threads even if they don't contain those exact words. How it works: Indexed HN posts and comments into PostgreSQL with pgvector (HNSW index) Embeddings generated with OpenAI's embedding model Queries run as nearest-neighbor vector searches — typical response under 50ms The whole thing runs on a single Postgres instance, no separate vector DB I…
Feb 2026 · ask.rivestack.io
- 18
Open-source search engine indexing infrastructure with inline SEO quality gates, fair multi-site scheduling, and rolling quota circuit breaker. - IndexFlowing/IndexFlow-core
9d ago · github.com
- 19AL
2022 · github.com
- 20RB
Happy to release FastPlaid, which aim to ease and accelerate ColBERT and ColPali retrieval
2025 · github.com
- 21IA
I built a "Thinking" IPFS in Rust. Unlike standard IPFS, IPFRS supports built-in Semantic Search (HNSW) & Logic Programming on the DAG. You can query content by meaning, not just hash. Looking for feedback on the architecture! Blog: https://medium.com/@kitasanio/beyond-static-storage-why-i-bu... Code: https://github.com/cool-japan/ipfrs #RustLang #IPFS #Web3 #AI #RAG
Jan 2026 · github.com
- 22WA
Witchcraft is from-scratch Rust reimplementation of Stanford's XTR-Warp (SIGIR'25, https://arxiv.org/abs/2501.17788 ) multi-vector semantic search engine. Witchcraft runs out of a single SQLite database, is blazing-fast (21ms p.95 end-to-end search latency on NFCorpus on a MacBook Pro), accurate (33% NDCG@10), and easy to deploy in your own apps. The Witchcraft repo also comes with Pickbrain, a sample app and agent skill that you can use to instantly query across all your Claude Code and Codex CLI sessions, effectively giving your agents global long-term memory. Please…
Apr 2026 · github.com
- 23LS
Feb 2026 · github.com
- 24VC
I’ve built vectorvector, an open-source CLI tool for working with elevation data. Key features: * Generates contour lines (vector), hillshade tiles (raster), and terrarium tiles (raster elevation) * Processes the entire planet in ~7 hours on consumer hardware * Algorithms: Marching Squares for contours, Horn for hillshade, and Ramer–Douglas–Peucker for line simplification Benchmarked on a MacBook Pro (M2, 64 GB RAM). Output is customizable and aimed at developers and GIS enthusiasts. Would love to hear your thoughts and feedback! Repo:…
2024 · github.com
Ranked by how close each launch is in meaning, then by votes. Refine with a description →