Vearch is a cloud-native distributed vector database for efficient similarity search of embedding vectors in your AI applications.
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Hybrid search: Both vector search and scalar filtering.
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Performance: Fast vector retrieval - search from millions of objects in milliseconds.
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Scalability & Reliability: Replication and elastic scaling out.
- VisualSearch: 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.
Add charts through the repo
$ helm repo add vearch https://vearch.github.io/vearch-helm
$ helm repo update && helm install my-release vearch/vearch
Add charts from local
$ git clone https://github.com/vearch/vearch-helm.git && cd vearch-helm
$ helm install my-release ./charts -f ./charts/values.yaml
Start by docker-compose
standalone mode
$ cd cloud
$ cp ../config/config.toml .
$ docker-compose --profile standalone up -d
cluster mode
$ cd cloud
$ cp ../config/config_cluster.toml .
$ docker-compose --profile cluster up -d
Deploy by docker: Quickly start with vearch docker image, please see DeployByDocker
Compile by source code: Quickly compile the source codes, please see SourceCompileDeployment
Vearch Architecture
Master: Responsible for schema management, cluster-level metadata, and resource coordination.
Router: Provides RESTful API: upsert, delete, search and query; request routing, and result merging.
PartitionServer (PS): 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.
Reference to cite when you use Vearch in a research paper:
@misc{li2019design,
title={The Design and Implementation of a Real Time Visual Search System on JD E-commerce Platform},
author={Jie Li and Haifeng Liu and Chuanghua Gui and Jianyu Chen and Zhenyun Ni and Ning Wang},
year={2019},
eprint={1908.07389},
archivePrefix={arXiv},
primaryClass={cs.IR}
}
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 protected].
Our slack : https://vearchworkspace.slack.com
Welcome to register the company name in this issue: #230 (in order of registration)
Licensed under the Apache License, Version 2.0. For detail see LICENSE and NOTICE.