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Vector Store Python Packages

Python packages with the GitHub topic vector-store. Sorted by monthly downloads, with stars and forks.
rapidsai
libraft-cu12

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

220K 1K 252
rapidsai
pylibraft-cu12

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

218K 1K 252
nvidia
libcuvs-cu12

cuVS - a library for vector search and clustering on the GPU

49K 864 241
rapidsai
raft-dask-cu12

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

47K 1K 252
nvidia
cuvs-cu12

cuVS - a library for vector search and clustering on the GPU

32K 864 241
rapidsai
libraft-cu13

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

25K 1K 252
rapidsai
pylibraft-cu13

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

25K 1K 252
nvidia
libcuvs-cu13

cuVS - a library for vector search and clustering on the GPU

19K 864 241
nvidia
cuvs-cu13

cuVS - a library for vector search and clustering on the GPU

10K 864 241
rapidsai
raft-dask-cu13

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

2K 1K 252
infino-ai
langchain-infino

LangChain partner package for Infino — vector, BM25, and hybrid (RRF) retrieval over one engine.

2K 0 0
i2mint
chromadol

Data Object Layer for ChromaDB

1K 1 0
oracle
oracle-vecdb

Python SDK for vector search, semantic search, RAG, embeddings, and AI agents on Oracle AI Database

1K 70 1
rapidsai
pylibraft-cu11

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

676 1K 252
KenyonY
flaxkv

🗲 A high-performance on-disk dictionary.

626 29 1
infino-ai
llama-index-vector-stores-infino

LlamaIndex integration for Infino — vector, BM25, hybrid (RRF), and SQL retrieval over one engine on object storage.

620 8 1
rapidsai
raft-dask-cu11

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

615 1K 252
rapidsai
cuvs-cu11

cuVS - a library for vector search and clustering on the GPU

586 866 241
rapidsai
libraft-cu11

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

414 1K 252
rapidsai
libcuvs-cu11

cuVS - a library for vector search and clustering on the GPU

405 866 241
crate
langchain-cratedb

CrateDB provider for LangChain.

382 3 1
KenyonY
flaxfile

🗲 A high-performance on-disk dictionary.

369 29 1
AdrianoKF
duckdb-haystack

Haystack document store and retriever for DuckDB VSS

248 0 0
wjddusrb03
langchain-turboquant

LangChain VectorStore with TurboQuant compression (ICLR 2026) - 6x memory reduction, training-free, no GPU required. The first LangChain integration for Google Research's TurboQuant algorithm.

226 1 2
    • Original data from PyPI, GitHub, and OSV; downloads served through ClickHouse
    • Sources & methodology