A Highly Scalable Distributed Vector Search Engine
What is Vald
Vald is a highly scalable distributed fast approximate nearest neighbor dense vector search engine.
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.
Vald's Main Features
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.
Vald distribute vector index to multiple agent, each agent stores different index.
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.
You can configure the number of vector dimension, the number of replica and etc.
Multi language supported
Golang, Java, Nodejs and python is supported.