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Top 23 Rust vector-database Projects
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MeiliSearch
A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.
Project mention: Lightning Memory-Mapped Database Manager (LMDB) 1.0 | news.ycombinator.com | 2026-07-02Yeah, and I also added support for parallel read your own writes where you can write tons of entries and spawn multi children read-only transactions from your writes where transaction and read from them in parallel.
We use this in Meilisearch [1] to post-process cache for our most common prefixes i.e., "w" will match "work", "word"... and computing this requires doing large unions of the documents matching those words.
Being able to do it in parallel is necessary, especially when you have billions of entries to operate on.
[1]: https://github.com/meilisearch/meilisearch
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qdrant
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
Project mention: Ask HN: What are some rock solid open source vector databases | news.ycombinator.com | 2026-06-22 -
memvid
Memory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.
Project mention: Show HN: I accidentally built "SQLite for AI memory" (Memvid) | news.ycombinator.com | 2026-01-05 -
databend
Data Agent Ready Warehouse : One for Analytics, Search, AI, Python Sandbox. — rebuilt from scratch. Unified architecture on your S3.
Check out what we're building at https://github.com/databendlabs/databend.
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RediSearch
A query and indexing engine for Redis, providing secondary indexing, full-text search, vector similarity search and aggregations.
This idea about communicating size/alignment is actually something we're doing on the port of RediSearch to Rust [0]. We have an "opaque sized type" which is declared on the Rust-side, and has its size & alignment communicated to the C-side via cbindgen. The C-side has no visibility into the fields, but it can still allocate it on the stack.
It's a bit ugly due to cbindgen not supporting const-generic expressions and macro-expansion being nightly-only. It seems like this will be a generally useful mechanism to be able to use values which are not traditionally FFI-safe across FFI boundaries.
[0]: https://github.com/RediSearch/RediSearch/blob/cfd364fa2a47eb...
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Project mention: Show HN: HelixDB – A Graph Database built on Object-storage | news.ycombinator.com | 2026-06-10
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pgvecto.rs
Scalable, Low-latency and Hybrid-enabled Vector Search in Postgres. Revolutionize Vector Search, not Database.
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VectorChord
Scalable, fast, and disk-friendly vector search in Postgres, the successor of pgvecto.rs.
- We support hybrid search with BM25 through https://github.com/tensorchord/VectorChord-bm25
The author simplifies the complexity of synchronizing between an existing database and a specialized vector database, as well as how to perform joint queries on them. This is also why we see most users choosing vector solution on PostgreSQL.
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EmbedAnything
Highly Performant, Modular, Memory Safe and Production-ready Inference, Ingestion and Indexing built in Rust 🦀
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duckle
Open-source local-first ETL/ELT studio: build visual data pipelines with 360+ components (dbt, data quality, CDC, streaming, SaaS APIs), run at native DuckDB speed, and generate pipelines from plain English with an on-device AI assistant. No cloud, no lock-in. (by slothflowlabs)
Project mention: Show HN: Duckle a drag-and-drop visual pipeline designer | news.ycombinator.com | 2026-06-22 -
Elasticsearch is a distributed search and analytics engine that stores data as JSON documents and lets you run fast full‑text search, aggregations, and log or metrics analysis across large datasets. Elasticsearch, prior to 7.11, used Apache License 2.0, a permissive license allowing commercial use, modification, and distribution with minimal restrictions. In January 2021, Elastic announced that starting with version 7.11, it would be relicensing its Apache 2.0 licensed code in Elasticsearch to be dual licensed under SSPL (Server-Side Public License) and the Elastic License, a strong copyleft license that requires anyone offering the software as a service to open-source the entire service stack. In August 2024, the GNU Affero General Public License was added to Elasticsearch version 8.16.0 as an option, making Elasticsearch free and open-source again. Elastic argued that large cloud providers were taking the open‑source Elasticsearch, offering it as a commercial managed service (e.g., Amazon Elasticsearch Service) and capturing much of the value without sufficient reciprocity. The license change was positioned as protecting Elastic’s SaaS/Elastic Cloud business and long‑term sustainability. OpenSearch was launched by AWS and partners as a fork later in 2021, based on Elasticsearch 7.10 and Kibana 7.10, the last Apache‑2.0 versions. Today, OpenSearch is no longer just an AWS side‑project; it is governed by the OpenSearch Software Foundation, a Linux Foundation project that provides vendor‑neutral governance and long‑term stewardship. Premier foundation members include AWS, SAP, and Uber, all of whom either run OpenSearch in production, build products on top of it, or contribute engineering resources. Among the benefits of switching to OpenSearch:
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Project mention: Is Grep All You Need? How Agent Harnesses Reshape Agentic Search | news.ycombinator.com | 2026-06-09
Combining regex filtering with semantic ranking using multi-vector embeddings has yielded good results for me. I use ColGREP from the LightOn team asa daily driver - https://github.com/lightonai/next-plaid/blob/main/colgrep/RE...
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oasysdb
In-memory vector store with efficient read and write performance for semantic caching and retrieval system. Redis for Semantic Caching.
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Project mention: Ahnlich, a fast lightweight similarity search engine | news.ycombinator.com | 2025-12-06
We've built ähnlich! A fast lightweight no-BS similarity search engine that runs in-memory. Docs are live at https://ahnlich.dev and we currently support Python, Rust and Go libraries
More than open to your contributions and usecases that I haven't considered at https://github.com/deven96/ahnlich
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duckle
Local-first ETL/ELT studio: a drag-and-drop visual pipeline designer that compiles to SQL and runs on DuckDB. Tiny desktop app, no servers, git-friendly workspaces.
- Git Integration
Duckle is delivered as a compact ~30 MB desktop application, ensuring no reliance on cloud services, servers, or vendor lock-in.
Explore the repository here:https://github.com/SouravRoy-ETL/duckle
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> Actually, you can implement HNSWs on disk, even if there are better data structures from the point of view of disk access latencies
I built a KV-backed HNSW in Rust using LMDB to address this exact usecase (https://github.com/nnethercott/hannoy). The trickiest part for sure is being clever with your IO ops since HNSW search requires tons of random reads to find the nearest neighbours. Especially if you're not on NVMe's (think EBS-based HNSW) you really start to feel the cost of those reads, even with all the fancy SIMD.
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VelesDB
The explainable, local-first memory engine for AI agents. One ~9 MB binary fuses vector + graph + columnar under VelesQL; why() returns the evidence path behind every recall. No cloud, no glue code — runs on server, browser, mobile and desktop.
Project mention: VelesDB now has a Haystack connector - build a RAG pipeline with zero infrastructure | dev.to | 2026-05-01VelesDB now ships a first-party Haystack 2.x DocumentStore, contributed by @CrepuscularIRIS in PR #672. Two pip installs, zero infrastructure, and your Haystack pipeline has a vector backend that runs in-process.
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sochdb
SochDB is a high-performance embedded, ACID-compliant vector database purpose-built for AI agents and memory
Project mention: Stop Reindexing: How We Built Real-Time Search Directly Into the Database using sochDB | dev.to | 2026-02-07In this post, I’ll explain why reindexing is fundamentally broken for real-time systems, and how we built SochDB to make search a native database capability instead of a separate infrastructure problem.
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bridgerust
High-performance infrastructure libraries built in Rust, with seamless bindings for Python, Node.js, and WebAssembly.
Two weeks ago, I published Embex to PyPI and npm.
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messy-folder-reorganizer-ai
🤖 AI-powered CLI for file reorganization. Runs fully locally — no data leaves your machine.
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
Rust vector-database discussion
Rust vector-database related posts
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A semantic Code Search CLI but with grep filters
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ColGREP: Semantic code search for your terminal and your coding agents
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Backing Up Spotify
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Elasticsearch: Mastering indexing, analyzers, and hybrid search
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BM25 in PostgreSQL – 3x Faster Than Elasticsearch
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AI, RAG and Vector Databases
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What should I do when someone blatantly copy my open-source project on GitHub?
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A note from our sponsor - SaaSHub
www.saashub.com | 20 Jul 2026
Index
What are some of the best open-source vector-database projects in Rust? This list will help you:
| # | Project | Stars |
|---|---|---|
| 1 | MeiliSearch | 58,615 |
| 2 | qdrant | 33,333 |
| 3 | memvid | 15,975 |
| 4 | databend | 9,388 |
| 5 | postgresml | 6,807 |
| 6 | RediSearch | 6,184 |
| 7 | helix-db | 5,634 |
| 8 | pgvecto.rs | 2,172 |
| 9 | VectorChord | 1,738 |
| 10 | EmbedAnything | 1,283 |
| 11 | duckle | 828 |
| 12 | mcp-server-elasticsearch | 694 |
| 13 | next-plaid | 517 |
| 14 | tinyvector | 433 |
| 15 | oasysdb | 376 |
| 16 | victor | 261 |
| 17 | ahnlich | 210 |
| 18 | duckle | 94 |
| 19 | hannoy | 84 |
| 20 | VelesDB | 75 |
| 21 | sochdb | 36 |
| 22 | bridgerust | 28 |
| 23 | messy-folder-reorganizer-ai | 20 |
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