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Top 23 vector-database Open-Source Projects
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anything-llm
Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience
Project mention: NVIDIA RTX Spark: What the Backlash Gets Wrong About AI on Your Desktop [2026] | dev.to | 2026-06-04The headline marketing number is "1 petaflop" of AI performance. Sounds staggering. Tim Carambat, creator of AnythingLLM and one of the most credible voices in the local AI developer community, has already questioned this figure. His point is one I've validated repeatedly in my own benchmarking: for running large language models locally, memory bandwidth is the actual bottleneck, not raw FLOPS. You can have all the tensor cores in the world, but if you can't feed them data fast enough, your Llama 3 inference is still going to crawl.
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SaaSHub
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llm-app
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.
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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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Milvus
Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search
Milvus: Optimized for large-scale, distributed memory operations
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Birdclaw is interesting because it gives agents access to a Twitter archive. [17] GBrain points at a personal recall layer around OpenClaw / Hermes-style workflows. [18] PageIndex is a useful reminder that simple retrieval, even BM25-only retrieval, still has a place. [19] The “RAG comeback in about 8 months” take lands because the archive problem is still unsolved in practice. [20]
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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 -
cognee
Cognee is the open-source AI memory platform for agents. Give your AI agents persistent long-term memory across sessions with a self-hosted knowledge graph engine.
Project mention: Hybrid vector + graph recall in pure TypeScript, zero dependencies | dev.to | 2026-07-07No multi-user server, no auth, no cloud sync, no document-ingestion pipeline. If you need those, Cognee and Mem0 are good platforms. rememori is for when you want memory inside your process, in five minutes, with nothing to operate.
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Weaviate
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
Project mention: Building KiroGraph: a 100% local semantic code knowledge graph for Kiro | dev.to | 2026-04-08More engines. The engine abstraction is clean, adding a new one means implementing four methods (initialize, upsert, search, count). Weaviate, Chroma, and Milvus are very interesting candidates. I should evaluate if they fit the ecosystem and what they offer as peculiarity. Maybe a "plugin system" would be a good implementation to let folks implement their preferred semantic engine.
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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 -
Project mention: Small AI Models Gain Traction In places with unreliable networks | news.ycombinator.com | 2026-07-07
100% agree on this.
I've been working on small local models for years with txtai (https://github.com/neuml/txtai). I've published close to 100 models that can run local for RAG, Agents, Vector Search and more (https://huggingface.co/NeuML/collections).
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LEANN
[MLsys2026]: RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.
Project mention: First lightweight local semantic search MCP for Claude Code | news.ycombinator.com | 2025-08-15@Berkeley SkyLab, we’re the first to bring semantic search to Claude Code with a fully local index in a novel, lightweight structure — check it out at LEANN(https://github.com/yichuan-w/LEANN).
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langchain4j
LangChain4j is an idiomatic, open-source Java library for building LLM-powered applications on the JVM. It offers a unified API over popular LLM providers and vector stores, and makes implementing tool calling (including MCP support), agents and RAG easy. It integrates seamlessly with enterprise Java frameworks like Quarkus and Spring Boot.
This post builds the small tool-using agent from Building Agentic Workflows in Java three ways: on the raw Anthropic Java SDK, on LangChain4j, and on Spring AI. We'll also touch the RAG pipeline from RAG From Scratch in Java — retrieval is exactly the kind of component a framework's tool abstraction is built to wrap. The goal isn't to crown a winner; it's to give you a way to make this decision for your own project instead of inheriting someone else's blog-post conclusion.
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claude-context
Code search MCP for Claude Code. Make entire codebase the context for any coding agent.
Claude Code doesn't do anything with semantic search or embeddings out of the box. They use a simple grep tool instead.
Neither does OpenAI's Codex CLI - you can confirm that by looking at the source code https://github.com/openai/codex
Cursor and Windsurf both use semantic search via embeddings.
You can get semantic search in Claude Code using this unofficial plugin: https://github.com/zilliztech/claude-context
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lancedb
Developer-friendly OSS embedded retrieval library for multimodal AI. Search More; Manage Less.
Project mention: Building KiroGraph: a 100% local semantic code knowledge graph for Kiro | dev.to | 2026-04-08LanceDB stores embeddings in Apache Lance columnar format. Columnar storage is efficient for batch reads and writes, which matters a lot during indexing. Pure JS, no native deps, sub-linear ANN search.
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orama
🌌 A complete search engine and RAG pipeline in your browser, server or edge network with support for full-text, vector, and hybrid search in less than 2kb.
Project mention: Building KiroGraph: a 100% local semantic code knowledge graph for Kiro | dev.to | 2026-04-08Orama does something clever: hybrid search. One query combines full-text relevance and vector similarity, which produces better results than running them separately and merging. Pure JS, no native compilation. If you want the best result quality and no native dependencies, Orama is the choice.
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Contributions and feedback — open an issue or PR on GitHub if you are hardening a Release Harness that includes the data plane; we are interested in what breaks when coding gets 10× faster but cluster validation does not.
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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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deeplake
Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training.
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deep-searcher
Open Source Deep Research Alternative to Reason and Search on Private Data. Written in Python.
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MariaDB
MariaDB server is a community developed fork of MySQL server. Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. (by MariaDB)
Project mention: As Oracle loses interest in MySQL, devs mull future options | news.ycombinator.com | 2026-01-23 -
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vector-database discussion
vector-database related posts
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Hybrid vector + graph recall in pure TypeScript, zero dependencies
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I gave my AI agent's memory a CI/CD pipeline
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Your AI Forgets Everything. Here's How Cognee Fixes It.
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What Building Anamnesis Taught Me About Giving AI a Memory
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Qwen 3.6 27B is the sweet spot for local development
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I gave an AI a memory of my interview history — here's what I learned building on Cognee
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Five Bugs Deep in an AI Memory Layer: My Week with Cognee
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A note from our sponsor - SaaSHub
www.saashub.com | 11 Jul 2026
Index
What are some of the best open-source vector-database projects? This list will help you:
| # | Project | Stars |
|---|---|---|
| 1 | anything-llm | 63,062 |
| 2 | llm-app | 59,138 |
| 3 | MeiliSearch | 58,476 |
| 4 | llama_index | 50,763 |
| 5 | Milvus | 45,068 |
| 6 | PageIndex | 33,921 |
| 7 | qdrant | 33,105 |
| 8 | cognee | 27,363 |
| 9 | Weaviate | 16,491 |
| 10 | memvid | 15,739 |
| 11 | txtai | 12,712 |
| 12 | LEANN | 12,633 |
| 13 | langchain4j | 12,515 |
| 14 | claude-context | 12,112 |
| 15 | lancedb | 10,833 |
| 16 | orama | 10,469 |
| 17 | oceanbase | 10,186 |
| 18 | databend | 9,378 |
| 19 | deeplake | 9,203 |
| 20 | deep-searcher | 7,911 |
| 21 | MariaDB | 7,805 |
| 22 | vespa | 7,001 |
| 23 | postgresml | 6,807 |