Vald

Highly scalable distributed vector search engine by Yahoo Japan.

Open SourceSelf HostedOffline Capable
0.0 (0)

About

Vald answers the question of how to run approximate nearest neighbor search over billions of vectors as a cloud-native service. Developed by LY Corporation, formerly Yahoo Japan, it is a distributed engine written in Go that runs on Kubernetes 1.19 or later and uses NGT, a graph and tree based ANN algorithm, at its core. The architecture splits into modular components: Agent pods that hold NGT indexes, load-balancing and filtering gateways, a Discoverer that tracks pods through the Kubernetes API, an Index Manager that coordinates automatic index rebuilds, and an optional Helm operator. This design provides horizontal scaling, automatic backups, and high availability so a node failure does not lose index data. Hosts need AVX2 support, and official client SDKs communicate over gRPC. Released under Apache 2.0 and listed in the CNCF landscape, it serves production workloads at LY Corporation and Japan Search, and suits platform teams who prefer operating vector search on their own Kubernetes clusters over managed databases.

Should you use Vald?

Pick it when

Pick Vald when a platform team already runs Kubernetes and needs a self-hosted, horizontally scaled ANN service for billions of vectors, with automatic index rebuilds, backups, and tolerance of node failures, accessed over gRPC.

Look elsewhere when

Skip it without Kubernetes expertise or AVX2 hosts: you operate agent, gateway, discoverer, and index manager components. Milvus is a distributed alternative with a managed tier, and Qdrant or pgvector are far simpler for smaller collections.

Alternatives to Vald

  • Milvus

    Cloud-native distributed vector database with a freemium managed tier; a similar scale target, with the option to hand operations to a hosted service.

  • Vespa

    Also billion-scale and self-hosted, adding full text search and ML ranking next to vectors; equally demanding to run, but more than ANN alone.

  • Qdrant

    Starts as one container and can cluster later; much easier to begin with than Vald's multi-component Kubernetes setup, with payload filtering built in.

  • FAISS

    If one service only needs the ANN algorithm, a library avoids running a cluster; you then handle sharding and availability yourself.

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Details

Price
Free
Platform
Local/Desktop
Difficulty
Advanced (4/5)
License
Apache-2.0
Added
Apr 3, 2026

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