The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense embedding, sparse embedding, tensor and full-text
Infinity is a cutting-edge AI-native database that provides a wide range of search capabilities for rich data types such as dense vector, sparse vector, tensor, full-text, and structured data. It provides robust support for various LLM applications, including search, recommenders, question-answering, conversational AI, copilot, content generation, and many more **RAG** (Retrieval-augmented Generation) applications.
- [Key Features](#-key-features)
- [Get Started](#-get-started)
- [Document](#-document)
- [Roadmap](#-roadmap)
- [Community](#-community)
## ⚡️ Performance
## 🌟 Key Features
Infinity comes with high performance, flexibility, ease-of-use, and many features designed to address the challenges facing the next-generation AI applications:
### 🚀 Incredibly fast
- Achieves 0.1 milliseconds query latency and 15K+ QPS on million-scale vector datasets.
- Achieves 1 millisecond latency and 12K+ QPS in full-text search on 33M documents.
> See the [Benchmark report](https://infiniflow.org/docs/dev/benchmark) for more information.
### 🔮 Powerful search
- Supports a hybrid search of dense embedding, sparse embedding, tensor, and full text, in addition to filtering.
- Supports several types of rerankers including RRF, weighted sum and **ColBERT**.
### 🍔 Rich data types
Supports a wide range of data types including strings, numerics, vectors, and more.
### 🎁 Ease-of-use
- Intuitive Python API. See the [Python API](https://infiniflow.org/docs/dev/pysdk_api_reference)
- A single-binary architecture with no dependencies, making deployment a breeze.
- Embedded in Python as a module and friendly to AI developers.
## 🎮 Get Started
This section provides guidance on deploying the Infinity database using Docker, with the client and server as separate processes.
### Prerequisites
- CPU: x86_64 with AVX2 support.
- OS:
- Linux with glibc 2.17+.
- Windows 10+ with WSL/WSL2.
- MacOS
- Python: Python 3.11+.
### Install Infinity server
#### Linux x86_64 & MacOS x86_64
```bash
sudo mkdir -p /var/infinity && sudo chown -R $USER /var/infinity
docker pull infiniflow/infinity:nightly
docker run -d --name infinity -v /var/infinity/:/var/infinity --ulimit nofile=500000:500000 --network=host infiniflow/infinity:nightly
```
#### Windows
If you are on Windows 10+, you must enable WSL or WSL2 to deploy Infinity using Docker. Suppose you've installed Ubuntu in WSL2:
1. Follow [this](https://learn.microsoft.com/en-us/windows/wsl/systemd) to enable systemd inside WSL2.
2. Install docker-ce according to the [instructions here](https://docs.docker.com/engine/install/ubuntu).
3. If you have installed Docker Desktop version 4.29+ for Windows: **Settings** **>** **Features in development**, then select **Enable host networking**.
4. Pull the Docker image and start Infinity:
```bash
sudo mkdir -p /var/infinity && sudo chown -R $USER /var/infinity
docker pull infiniflow/infinity:nightly
docker run -d --name infinity -v /var/infinity/:/var/infinity --ulimit nofile=500000:500000 --network=host infiniflow/infinity:nightly
```
### Install Infinity client
```
pip install infinity-sdk==0.7.2
```
### Run a vector search
```python
import infinity
infinity_obj = infinity.connect(infinity.NetworkAddress("", 23817))
db_object = infinity_object.get_database("default_db")
table_object = db_object.create_table("my_table", {"num": {"type": "integer"}, "body": {"type": "varchar"}, "vec": {"type": "vector, 4, float"}})
table_object.insert([{"num": 1, "body": "unnecessary and harmful", "vec": [1.0, 1.2, 0.8, 0.9]}])
table_object.insert([{"num": 2, "body": "Office for Harmful Blooms", "vec": [4.0, 4.2, 4.3, 4.5]}])
res = table_object.output(["*"])
.match_dense("vec", [3.0, 2.8, 2.7, 3.1], "float", "ip", 2)
.to_pl()
print(res)
```
## 🔧 Deploy Infinity using binary
If you wish to deploy Infinity using binary with the server and client as separate processes, see the [Deploy infinity using binary](https://infiniflow.org/docs/dev/deploy_infinity_server) guide.
## 🔧 Build from Source
See the [Build from Source](https://infiniflow.org/docs/dev/build_from_source) guide.
## 📚 Document
- [Quickstart](https://infiniflow.org/docs/dev/)
- [Python API](https://infiniflow.org/docs/dev/pysdk_api_reference)
- [HTTP API](https://infiniflow.org/docs/dev/http_api_reference)
- [References](https://infiniflow.org/docs/dev/category/references)
- [FAQ](https://infiniflow.org/docs/dev/FAQ)
## 📜 Roadmap
See the [Infinity Roadmap 2025](https://github.com/infiniflow/infinity/issues/2393)
## 🙌 Community
- [Discord](https://discord.gg/jEfRUwEYEV)
- [Twitter](https://twitter.com/infiniflowai)
- [GitHub Discussions](https://github.com/infiniflow/infinity/discussions)