A vector index built on TurboQuant, written in Rust with Python bindings
- ann
- avx512
- embeddings
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A vector index built on TurboQuant, written in Rust with Python bindings
Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk
[MLsys2026 Best Paper]: https://arxiv.org/abs/2506.08276. RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.
💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows
Data Agent Ready Warehouse : One for Analytics, Search, AI, Python Sandbox. — rebuilt from scratch. Unified architecture on your S3.
Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training.
Open Lakehouse Format for Multimodal AI. Convert from Parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, and PyTorch with more integrations coming..
Header-only C++/python library for fast approximate nearest neighbors
An open lakehouse engine — Postgres-native, vector-native and Python-native. Speaks PostgreSQL, runs on your object storage, written in Rust.
The AI-Native Search Database. Best for agent storage, it unifies vector, text, structured, and semi-structured data into a single engine. This all-in-one database makes agents smarter, easier to run, and more stable.
MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog, HyperLogLog++, LSH Ensemble and HNSW
Distributed vector search for AI-native applications
Official library for RaBitQ vector quantization and approximate nearest-neighbor search, in C++ and Python.
A c++ toolbox of locality-sensitive hashing (LSH), provides several popular LSH algorithms, also support python and matlab.