Skip to main content
0
I

Infinity

The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense

Rating

0.0

Votes

0

score

Downloads

0

total

Price

Free

No login needed

Works With

Claude CodeCursorWindsurfVS CodeDeveloper tool

About

The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense embedding, sparse embedding, tensor and full-text

Document | Benchmark | Twitter | Discord

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.

⚡️ 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 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
  • 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:

Don't lose this

Three weeks from now, you'll want Infinity again. Will you remember where to find it?

Save it to your library and the next time you need Infinity, it’s one tap away — from any AI app you use. Group it into a bench with the rest of the team for that kind of task and you can pull the whole stack at once.

⚡ Pro tip for geeks: add a-gnt 🤵🏻‍♂️ as a custom connector in Claude or a custom GPT in ChatGPT — one click and your library is right there in the chat. Or, if you’re in an editor, install the a-gnt MCP server and say “use my [bench name]” in Claude Code, Cursor, VS Code, or Windsurf.

🤵🏻‍♂️

a-gnt's Take

Our honest review

This plugs directly into your AI and gives it new abilities it didn't have before. The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense . Once connected, just ask your AI to use it. It's completely free and works across most major AI apps. This one just landed in the catalog — worth trying while it's fresh.

Tips for getting started

1

Tap "Get" above, pick your AI app, and follow the steps. Most installs take under 30 seconds.

2

Your data stays between you and your AI — nothing is shared with us or anyone else.

What's New

Version 1.0.06 days ago

Imported from GitHub

Ratings & Reviews

0.0

out of 5

0 ratings

No reviews yet. Be the first to share your experience.