vald
nmslib
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| vald | nmslib | |
|---|---|---|
| 13 | 4 | |
| 1,453 | 3,278 | |
| 1.2% | 1.2% | |
| 9.4 | 0.0 | |
| 7 days ago | about 1 month ago | |
| Go | C++ | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
vald
- What is the reason for using go mod replace like this?
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Top 10 Best Vector Databases & Libraries
Vald (1.2k ⭐) → A highly scalable distributed fast approximate nearest neighbor dense vector search engine. Vald is designed and implemented based on the Cloud-Native architecture. It uses the fastest ANN Algorithm NGT to search neighbors. Vald has automatic vector indexing and index backup, and horizontal scaling which made for searching from billions of feature vector data.
- open-source google-like search for workplace knowledge
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[P] Embeddinghub: A vector database built for ML embeddings
Another approximate nearest neighbor system to look at: https://vald.vdaas.org/
- Vector Search Indexes
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Vald: a highly scalable distributed fast approximate nearest neighbour dense vector search engine.
Web: https://vald.vdaas.org
GitHub: https://github.com/vdaas/vald
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Hacker News top posts: Apr 9, 2021
Vald: A Highly Scalable Distributed Vector Search Engine\ (26 comments)
- Vald: A Highly Scalable Distributed Vector Search Engine
nmslib
- Vector search just got up to 10x faster and vertically scalable
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The Missing ”WHERE” Clause for Vector Search
Amazon's Opensearch (fork of Elasticsearch) natively supports vector-based approximate KNN (using https://github.com/nmslib/nmslib/) which is integrated with Opensearch's native filtering functionality. Elasticsearch also has similar functionality, but I don't know if their KNN code scales quite as well.
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Vector Search Indexes
nmslib (https://github.com/nmslib/nmslib) supports sparse vectors for some of its spaces. It has fewer indexing methods than faiss, though.
https://github.com/nmslib/nmslib/blob/master/manual/spaces.m...
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Are there more practical tools for KNN searches and storing documents/embeddings?
I also needed to build a similar system and I used nmslib, maybe check it out - https://github.com/nmslib/nmslib
What are some alternatives?
Milvus - A cloud-native vector database, storage for next generation AI applications
faiss - A library for efficient similarity search and clustering of dense vectors.
pgvector - Open-source vector similarity search for Postgres
Weaviate - Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
TorchPQ - Approximate nearest neighbor search with product quantization on GPU in pytorch and cuda
hora - 🚀 efficient approximate nearest neighbor search algorithm collections library written in Rust 🦀 .
alvd - alvd = A Lightweight Vald. A lightweight distributed vector search engine works without K8s.
qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
ann-benchmarks - Benchmarks of approximate nearest neighbor libraries in Python
knowhere - Knowhere is an open-source vector search engine, integrating FAISS, HNSW, etc.