What is InfinityFlow?

Infinity is an AI-native database designed for large language model applications. It delivers hybrid search across dense and sparse embeddings, tensors, and full‑text, with optional filtering and reranking via RRF, weighted sum, or ColBERT. The system achieves 0.

1 ms query latency and supports up to 15 K queries per second on million‑scale vector collections. Data types include strings, numerics, and vectors, enabling diverse data storage. Developers benefit from an intuitive Python API and a single‑binary deployment that requires no external dependencies.

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InfinityFlow's key features

0.1 ms query latency
15K QPS throughput
Hybrid dense sparse tensor search
Supports RRF weighted rerankers
Wide range data types
Intuitive Python API
Single-binary no dependencies

InfinityFlow use cases

Build a real-time recommendation engine for e-commerce, using hybrid dense‑sparse vector search to match user browsing patterns with product embeddings and deliver sub‑100 ms personalized upsell suggestions
Create a semantic search layer for enterprise knowledge bases, combining full‑text indexing with ColBERT reranking to surface contextually relevant policy documents and technical specs for internal chatbots
Develop a data‑science pipeline that stores and queries high‑dimensional image embeddings, enabling rapid similarity search for anomaly detection and clustering at 15 k qps