Vearch is a scalable distributed system for efficient similarity search of deep learning vectors.
space, documents, vectors, scalars
Responsible for schema mananagement, cluster-level metadata, and resource coordination.
Provides RESTful API:
update ; request routing, and result merging.
Hosts document partitions with raft-based replication.
Gamma is the core vector search engine implemented based on faiss. It provides the ability of storing, indexing and retrieving the vectors and scalars.
Quickly build a distributed vector search system with RESTful API, please see docs/Deploy.md.
Vearch can be leveraged to build a complete visual search system to index billions of images. The image retrieval plugin for object detection and feature extraction is also required. For more information, please refer to docs/Quickstart.md.
Jie Li, Haifeng Liu, Chuanghua Gui, Jianyu chen, Zhenyun Ni, Ning Wang, Yuan Chen. The Design and Implementation of a Real Time Visual Search System on JD E-commerce Platform. In the 19th International ACM Middleware Conference, December 10–14, 2018, Rennes, France. https://arxiv.org/abs/1908.07389
You can report bugs or ask questions in the issues page of the repository.
For public discussion of Vearch or for questions, you can also send email to email@example.com.
Licensed under the Apache License, Version 2.0. For detail see LICENSE and NOTICE.