https://github.com/bridgerust/bridgerust
High-performance infrastructure libraries built in Rust, with seamless bindings for Python, Node.js, and WebAssembly.
https://github.com/bridgerust/bridgerust
ai ai-agent bindings chromadb embeddings lancedb machine-learning napi-rs nodejs orm pinecode pyo3 python qdrant rag rust rust-bindings semantic-search vector-database weaviate
Last synced: 30 days ago
JSON representation
High-performance infrastructure libraries built in Rust, with seamless bindings for Python, Node.js, and WebAssembly.
- Host: GitHub
- URL: https://github.com/bridgerust/bridgerust
- Owner: bridgerust
- Created: 2025-12-25T12:02:29.000Z (about 2 months ago)
- Default Branch: main
- Last Pushed: 2026-01-11T00:03:02.000Z (about 1 month ago)
- Last Synced: 2026-01-11T07:10:01.018Z (about 1 month ago)
- Topics: ai, ai-agent, bindings, chromadb, embeddings, lancedb, machine-learning, napi-rs, nodejs, orm, pinecode, pyo3, python, qdrant, rag, rust, rust-bindings, semantic-search, vector-database, weaviate
- Language: Rust
- Homepage: https://bridgerust.dev
- Size: 1.39 MB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 10
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: docs/CONTRIBUTING.md
Awesome Lists containing this project
README
# Embex
[![PyPI Downloads]()](https://pepy.tech/projects/embex)
[](https://www.npmjs.com/package/@bridgerust/embex)
[](https://github.com/bridgerust/bridgerust)
[](https://discord.gg/ZvNAeaWN)
[Why Embex?](#the-problem) - [Quick Start](#get-started-in-60-seconds) - [Docs](https://bridgerust.dev/embex) - [Discord](https://discord.gg/ZvNAeaWN) - [Examples](#what-developers-are-building)
## The Problem
Every vector database has a different API:
```python
# Pinecone
index.upsert(vectors=[(id, values, metadata)])
results = index.query(vector=query, top_k=5)
# Qdrant
client.upsert(collection_name=name, points=points)
results = client.search(collection_name=name, query_vector=query, limit=5)
# Weaviate
client.data_object.create(data_object, class_name)
results = client.query.get(class_name).with_near_vector(query).do()
```
Switching providers = **rewriting your entire codebase**.
## The Solution
One API. Seven databases:
```python
# Works with ANY provider
await client.collection("products").insert(vectors)
results = await client.collection("products").search(vector=query, top_k=5)
```
Switch from LanceDB to Qdrant? **Change one line**:
```diff
- client = await EmbexClient.new_async(provider="lancedb", url="./data")
+ client = await EmbexClient.new_async(provider="qdrant", url="http://localhost:6333")
```
**👇 See it in action:**
## Real Migration Example
Sarah built a RAG chatbot with Pinecone. 6 months later, costs hit $500/mo.
**With traditional clients:** 2-3 days rewriting code + testing
**With Embex:** 2 minutes changing config
```python
# Before (Pinecone-specific)
from pinecone import Pinecone
pc = Pinecone(api_key="...")
index = pc.Index("products")
# After (Embex)
from embex import EmbexClient
client = await EmbexClient.new_async(
provider="qdrant", # Changed from "pinecone"
url=os.getenv("QDRANT_URL")
)
```
**Result:** Same functionality. $450/mo saved. Zero code changes.
## Why Rust Core Matters
Pure Python/JS vector operations are slow. Embex uses Rust with SIMD acceleration:
| Operation | Pure Python | Embex (Rust) | Speedup |
| --------------------------------- | ----------- | ------------ | -------- |
| Vector normalization (Batch 1000) | 45ms | 11ms | **4.1x** |
| Cosine similarity (Batch 1000) | 230ms | 58ms | **4.0x** |
| Metadata filtering | 180ms | 42ms | **4.3x** |
_Benchmarked on M1 Max, average of 1000 runs_
The difference compounds: **4x faster operations** × **thousands of vectors** = significant time saved.
## Provider Benchmarks
Real-world performance vs native Python clients (10k vectors, 384d):
| Provider | Client | Insert (ops/s) | Speedup | Search Latency |
| :----------- | :-------- | :------------- | :------- | :------------- |
| **Qdrant** | **Embex** | **24,825** | **4.3x** | **1.95ms** |
| | Native | 5,754 | | 4.69ms |
| **Weaviate** | **Embex** | **5,163** | **4.1x** | **1.77ms** |
| | Native | 1,256 | | 4.03ms |
| **Chroma** | Embex | 3,136 | 1.0x | 3.97ms |
| | Native | 3,077 | | 3.46ms |
## What Developers Are Building
🤖 **AI Chatbots with Memory**
Store conversation history for context-aware responses
🔍 **Semantic Search Engines**
Search documentation, code, or content by meaning, not keywords
🎯 **Recommendation Systems**
E-commerce product recommendations with embeddings
📚 **Knowledge Bases**
RAG systems for internal documentation and support
🎨 **Image Search**
Find similar images using vision embeddings
> "Embex let me prototype with LanceDB locally, then deploy to Qdrant Cloud without changing a line of code. Saved 2 days of migration work."
[Share what you built →](https://github.com/bridgerust/bridgerust/discussions)
## Get Started in 60 Seconds
**Python:**
```bash
# Install
pip install embex lancedb sentence-transformers
# Quick test
python3 << EOF
import asyncio
from embex import EmbexClient
async def main():
client = await EmbexClient.new_async('lancedb', './data')
print('✅ Embex ready!')
asyncio.run(main())
EOF
```
**Node.js:**
```bash
npm install @bridgerust/embex lancedb
node -e "
const {EmbexClient} = require('@bridgerust/embex');
EmbexClient.new({provider: 'lancedb', url: './data'})
.then(() => console.log('✅ Embex ready!'));
"
```
→ **Next:** See [**Getting Started Guide**](https://bridgerust.dev/embex/quickstart)
## Embex vs. Alternatives
| Feature | Raw Clients | LangChain | LlamaIndex | **Embex** |
| --------------------------------- | ----------- | --------- | ---------- | ---------------- |
| Universal API | ❌ | ✅ | ✅ | ✅ |
| Switch providers (0 code changes) | ❌ | ❌ | ❌ | ✅ |
| Performance (Rust core) | ⚡ Fast | 🐌 Slow | 🐌 Slow | ⚡ **4x Faster** |
| Zero Docker setup | Varies | ❌ | ❌ | ✅ (LanceDB) |
| Connection pooling | Manual | ❌ | ❌ | ✅ |
| Local development | Complex | Complex | Complex | ✅ (LanceDB) |
| Production ready | ✅ | ⚠️ | ⚠️ | ✅ |
**When to use each:**
- **Raw clients:** You're committed to one database forever
- **LangChain/LlamaIndex:** You need full RAG framework with LLM chains
- **Embex:** You want vector operations only, with flexibility to switch providers
## Supported Providers
LanceDB • Qdrant • Pinecone • Chroma • PgVector • Milvus • Weaviate
## Development → Production Roadmap
| Stage | Recommendation | Why? |
| :------------------ | :-------------------- | :---------------------------------- |
| **Day 1: Learning** | **LanceDB** | Runs locally. No Docker. Free. |
| **Week 2: Staging** | **Qdrant / Pinecone** | Managed cloud. Connection pooling. |
| **Month 1: Scale** | **Milvus** | Billion-scale vectors. Distributed. |
| **Anytime** | **PgVector** | You already use PostgreSQL. |
## Community
- 💬 **Discord:** Get help, share projects, discuss features → [Join Server](https://discord.gg/ZvNAeaWN)
- � **Reddit:** Join the discussion → [r/embex](https://www.reddit.com/r/embex/)
- �💡 **GitHub Discussions:** Feature requests and Q&A
- 🐛 **Issues:** Bug reports
- 📝 **Blog:** Tutorials and case studies → [bridgerust.dev/embex](https://bridgerust.dev/embex/introduction)
**Built something cool with Embex?** Share it in #showcase on Discord or tag us on Twitter!
## FAQ
**Q: How is Embex different from LangChain's VectorStores?**
A: LangChain couples vector operations with LLM chains. Embex is vector-only, 4x faster (Rust core), and switching providers requires 0 code changes (vs. rewriting VectorStore initialization).
**Q: Does Embex support hybrid search (vector + keyword)?**
A: Yes! Coming in v0.3. Currently supports pure vector and metadata filtering.
**Q: Can I use Embex in production?**
A: Yes! Embex includes production features like connection pooling, automatic retries, and observability hooks. Currently used in production by developers running RAG chatbots, semantic search engines, and recommendation systems. See [deployment guide](https://bridgerust.dev/embex/deployment) for best practices.
**Q: Which provider should I start with?**
A: LanceDB for local dev (zero setup), then Qdrant/Pinecone for production (managed, scalable).
**Q: Do you support [X database]?**
A: Current: LanceDB, Qdrant, Pinecone, Chroma, PgVector, Milvus, Weaviate. Roadmap: Elasticsearch, OpenSearch, Redis. [Request here](https://github.com/bridgerust/bridgerust/issues).
## Installation
### Python
```bash
pip install embex
```
### Node.js
```bash
npm install @bridgerust/embex
```
### Rust (Development)
```toml
[dependencies]
bridge-embex = { git = "https://github.com/bridgerust/bridgerust", path = "crates/embex/client" }
```
## Features
- **Universal API**: Switch providers without code changes
- **High Performance**: Rust core with SIMD acceleration (4x faster)
- **Zero Setup**: Start with LanceDB (embedded, local)
- **Production Ready**: Connection pooling, migrations, observability
## Documentation
- [**Getting Started**](https://bridgerust.dev/embex/quickstart)
- [**API Reference**](https://bridgerust.dev/embex/api-reference)
- [**Providers Guide**](https://bridgerust.dev/embex/providers)
## 🚀 Next Steps
1. ⭐ **Star this repo** if Embex saves you time
2. 💬 **Join Discord** for help and to share what you build
3. 📖 **Try the tutorial:** [Build a chatbot in 10 minutes](https://bridgerust.dev/embex/tutorial)
**Quick links:**
- [Installation Guide](https://bridgerust.dev/embex/installation)
- [Python API Docs](https://bridgerust.dev/embex/api/python) • [Node.js API Docs](https://bridgerust.dev/embex/api/nodejs)
- [Migration Examples](https://bridgerust.dev/embex/migrations)
- [Performance Benchmarks](https://bridgerust.dev/embex/benchmarks)
## BridgeRust Framework
This repository also contains the **BridgeRust** framework - a unified system for building cross-language Rust libraries. Embex is built with BridgeRust.
### Packages & Status
| Crate | Version | Downloads | Docs |
| :------------------------------------------------ | :---------------------------------------------------------------------------------------------------------------- | :---------------------------------------------------------------------------------------------------------------- | :------------------------------------------------------------------------------------------------------ |
| **[bridgerust](crates/bridgerust)** | [](https://crates.io/crates/bridgerust) | [](https://crates.io/crates/bridgerust) | [](https://bridgerust.dev/bridgerust/introduction) |
| **[bridgerust-macros](crates/bridgerust-macros)** | [](https://crates.io/crates/bridgerust-macros) | [](https://crates.io/crates/bridgerust-macros) | [](https://docs.rs/bridgerust-macros) |
| **[bridge (CLI)](cli/bridge)** | [](https://crates.io/crates/bridge) | [](https://crates.io/crates/bridge) | - |
### Framework Documentation
- [Quick Reference](docs/QUICK_REFERENCE.md)
- [Getting Started Guide](docs/getting-started-bridgerust.md)
- [Migration Guide](docs/MIGRATION_GUIDE.md)
- [Examples](docs/EXAMPLES.md)
- [Troubleshooting](docs/TROUBLESHOOTING.md)
- [Comprehensive Example](examples/bridgerust-example/)
## Contributing
See [CONTRIBUTING.md](docs/CONTRIBUTING.md) for development setup and guidelines.
## License
MIT OR Apache-2.0
[](LICENSE)