#19 · Primary category: Vector Databases

infinity

ai-native approximate-nearest-neighbor-search bm25 cpp20 cpp20-modules embedding full-text-search hnsw hybrid-search information-retrival multi-vector nearest-neighbor-search rag search-engine tensor-database vector vector-database vector-search vectordatabase

The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.

Project last updated:08/27/26

GitHub Stars

4.7K

Forks

441

Contributors

54

License

Apache-2.0

Why we included this project

Infinity is a database built around hybrid search: it runs dense and sparse vector, tensor, and full-text queries in one engine, and lets you blend the results with built-in rerankers like RRF or ColBERT instead of writing that logic yourself. That combination matters for retrieval-heavy LLM apps such as RAG, copilots, and question answering, where you often want both semantic similarity and exact keyword matching on the same data. The single-binary design with no external dependencies and a Python API keeps deployment simple, whether you embed it in your app or run it as a server. If you're building a proof of concept for hybrid retrieval and want to compare it against a hand-rolled stack, it's a convenient starting point.

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