#19 · Primary category: Vector Databases
infinity
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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