Infinity

Infinity is an AI-native database for LLM applications that executes hybrid searches across dense vector, sparse vector, tensor, and full-text data types.

Infinity functions as an AI-native database specifically designed for large language model applications. It provides hybrid search capabilities by combining dense embedding, sparse embedding, tensor, and full-text search methods with filtering options. The system supports various reranking techniques such as RRF, weighted sum, and ColBERT. Users interact with the database through a Python API. Designed for straightforward deployment, the architecture is a single-binary with no dependencies. It supports multiple data types including strings, numerics, and vectors to handle diverse application requirements.

Infinity at a glance

Best for: Software engineer
Pricing: Free
Released: July 2022
Category: AI coding tool
Website: infiniflow.org

Key features

Hybrid search of dense, sparse, tensor, and full-text data
Query latency of 0.1 milliseconds on million-scale datasets
Support for RRF, weighted sum, and ColBERT rerankers
Single-binary architecture with no dependencies
Python API for data interaction
Support for string, numeric, and vector data types

Use it for

Building high-performance LLM application backends
Executing hybrid search over large-scale vector datasets
Implementing custom reranking logic for AI models

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