awesomegolang / vald

Vald. A Highly Scalable Distributed Vector Search Engine

What is Vald?

Vald is a highly scalable distributed fast approximate nearest neighbor (ANN) dense vector search engine.

Vald is designed and implemented based on Cloud-Native architecture.

Vald has automatic vector indexing and index backup, and horizontal scaling which made for searching from billions of feature vector data.

Vald is easy to use, feature-rich and highly customizable as you needed.

It uses the fastest ANN Algorithm NGT to search neighbors.

(If you are interested in ANN benchmarks, please refer to ann-benchmarks.com.)

For more information, please refer to Official Web Site.

Vald can handle any object data, image, audio processing, video, text, binary, or etc., if converting to the vector, and be used for:

• Recognition
• Recommendation
• Detecting
• Grammar checker
• Real-time translator
• also you want to do!

Requirements

• Kubernetes 1.19~
• AVX2 instructions (required by Vald Agent NGT)

Get Started

Go to Get Started page to try out Vald !

Installation

Using Helm

helm repo add vald https://vald.vdaas.org/charts
helm install vald-cluster vald/vald

If you use the default values.yaml, the nightly images will be installed.

Using Helm-operator

Please refer to vald-helm-operator.

Components

Component	Docker image	latest image	nightly image
Agent NGT
Agent Sidecar
Discoverer
Gateways
Index Manager
Helm Operator

Docker images tagging policy:

• nightly ... latest build of main branch
• vX.X.X ... released versions
• latest ... latest build of release versions
• stable ... latest long-term supported version

Tools

• SDK: Official client libraries
• Demo: Demo repository using sample data

Vald Users

       

Contribution

Please read the contribution guide.

Before your first commit to this repository, it is strongly recommended to run the commands below.

git clone https://github.com/vdaas/vald && cd vald
make init

Contributors

Thanks goes to these wonderful people (emoji key):

Yusuke Kato 💻 🎨 🚧 📆	Rintaro Okamura 💻 📖 🚧 📦	Kosuke Morimoto 💻 💡 🔧 ⚠️	Kiichiro YUKAWA 📖 🚧 ⚠️ ✅	datelier 💻 🤔	Kevin Diu 📖 💡 ⚠️ ✅	Hiroto Funakoshi 📖 🔧 ⚠️ ✅
taisho 🎨 📖 💡	Pierre Grimaud 📖	Omer Katz 📖 ✅	Koichi Shiraishi ️️️️♿️	Siyuan Liu ️️️️♿️ 💡	David Calvert 📖

LICENSE

vald released under Apache 2.0 license, refer LICENSE file.