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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

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!


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

Get Started

Go to Get Started page to try out Vald !


Using Helm

helm repo add vald
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.


Component Docker image latest image nightly image
Agent NGT
Agent Sidecar

Index Manager
Helm Operator

Docker images tagging policy:

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


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

Vald Users

yahoojapan         jpsearch


Please read the contribution guide.

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

git clone && cd vald
make init


All Contributors

Thanks goes to these wonderful people (emoji key):

Yusuke Kato

💻 🎨 🚧 📆

Rintaro Okamura

💻 📖 🚧 📦

Kosuke Morimoto

💻 💡 🔧 ⚠️

Kiichiro YUKAWA

📖 🚧 ⚠️


💻 🤔

Kevin Diu

📖 💡 ⚠️

Hiroto Funakoshi

📖 🔧 ⚠️


🎨 📖 💡

Pierre Grimaud


Omer Katz


Koichi Shiraishi


Siyuan Liu

️️️️♿️ 💡

David Calvert



vald released under Apache 2.0 license, refer LICENSE file.

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