A Highly Scalable Distributed Vector Search Engine

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

  • Asynchronize Auto Indexing

    Usually the graph requires locking during indexing, which cause stop-the-world. But Vald uses distributed index graph so it continues to work during indexing.

  • Customizable Ingress/Egress Filtering

    Vald implements it's own highly customizable Ingress/Egress filter. Which can be configured to fit the gRPC interface.

  • Cloud-native based vector searching engine

    Horizontal scalable on memory and cpu for your demand.

  • Auto Indexing Backup

    Vald supports to auto backup feature using Object Storage or Persistent Volume which enables disaster recovery.

  • Distributed Indexing

    Vald distribute vector index to multiple agent, each agent stores different index.

  • Index Replication

    Vald stores each index in multiple agents which enables index replicas. Automatically rebalance the replica when some Vald agent goes down.

  • Easy to use

    Vald can be easily installed in a few steps.

  • Highly customizable

    You can configure the number of vector dimension, the number of replica and etc.

  • Multi language supported

    Golang, Java, Nodejs and python is supported.