{"data":{"slug":"vdaas-vald","name":"vald","tagline":"A Highly Scalable Distributed Vector Search Engine","github_url":"https://github.com/vdaas/vald","owner":"vdaas","repo":"vald","owner_avatar_url":"https://avatars.githubusercontent.com/u/45956367?v=4","primary_language":"Go","stars":1728,"forks":95,"topics":["anng","approximate-nearest-neighbor-search","cloud","cloud-native","distributed-systems","golang","hacktoberfest","high-dimensional-data","high-performance","image-search","image-search-engine","kubernetes","microservices","nearest-neighbor-search","ngt","similarity-search","vald","vector","vector-search-engine"],"archived":false,"github_pushed_at":"2026-09-16T04:37:50+00:00","maintenance_label":"Very active","stars_delta_30d":14,"url":"https://www.graphcanon.com/tools/vdaas-vald","markdown_url":"https://www.graphcanon.com/tools/vdaas-vald.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/vdaas-vald","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=vdaas-vald","description":"Vald.  A Highly Scalable Distributed Vector Search Engine","homepage_url":"https://vald.vdaas.org","license":"Apache-2.0","open_issues":147,"watchers":15,"ai_summary":"Vald is a distributed vector search engine written in Go, designed for high performance and scalability, suitable for applications like image search and similarity search.","readme_excerpt":"## Requirements\n\n- Kubernetes 1.19~\n- AVX2 instructions (required by Vald Agent NGT)\n\n---\n\n## LICENSE\n\nVald released under Apache 2.0 license, refer [LICENSE](https://github.com/vdaas/vald/blob/main/LICENSE) file.","github_created_at":"2019-07-07T06:42:22+00:00","created_at":"2026-07-11T23:19:39.540711+00:00","updated_at":"2026-09-20T04:31:26.514577+00:00","categories":[{"slug":"data-retrieval","name":"Data & Retrieval","url":"https://www.graphcanon.com/categories/data-retrieval","markdown_url":"https://www.graphcanon.com/categories/data-retrieval.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/data-retrieval"},{"slug":"vector-databases","name":"Vector Databases","url":"https://www.graphcanon.com/categories/vector-databases","markdown_url":"https://www.graphcanon.com/categories/vector-databases.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/vector-databases"}],"tags":[{"slug":"anng","name":"anng"},{"slug":"approximate-nearest-neighbor-search","name":"approximate-nearest-neighbor-search"},{"slug":"cloud-native","name":"cloud-native"},{"slug":"distributed-systems","name":"distributed-systems"},{"slug":"golang","name":"golang"},{"slug":"high-dimensional-data","name":"high-dimensional-data"},{"slug":"image-search","name":"image-search"},{"slug":"kubernetes","name":"kubernetes"}],"trust":{"provenance":{"is_fork":false,"github_id":195619075,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-18T08:31:38.480Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":1,"days_since_push":2,"last_release_at":"2026-08-26T06:00:26Z","stars_delta_30d":14,"open_issues_delta_30d":1},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-09-18T08:31:40.107Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-18T08:31:37.386Z"},"languages":{"value":["go"],"source":"github.language","observed_at":"2026-09-18T08:31:37.386Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-09-18T08:31:37.386Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":{"notes":["Requires Kubernetes 1.19 or newer.","Hardware must support AVX2 instructions for optimal performance."],"min_ram_gb":null,"requires_docker":false},"constraints":{"min_ram_gb":null,"requires_docker":false},"when_to_use":["When you need a scalable solution for high-dimensional data search, Vald can handle large volumes of data efficiently.","If your application requires integration with Kubernetes, Vald is designed to work seamlessly within a Kubernetes environment.","For applications that demand high performance and can benefit from AVX2 instructions, Vald's Vald Agent NGT component can provide a significant speed boost."],"when_not_to_use":["Avoid Vald if your infrastructure does not support Kubernetes 1.19 or newer, as it is a requirement for Vald's operation.","Do not use Vald if your hardware does not support AVX2 instructions, as this will limit the performance of the Vald Agent NGT component.","If your project requires a non-distributed solution, Vald's distributed architecture might introduce unnecessary complexity."],"source":"enrich:decision_facts","observed_at":"2026-09-18T10:23:34.776Z"},"constraint_facets":{"min_ram_gb":null,"requires_docker":false},"decision_summary":[{"label":"Requirements","value":"Requires Kubernetes 1.19 or newer.; Hardware must support AVX2 instructions for optimal performance."},{"label":"Adopt for","value":"Vald is a distributed vector search engine written in Go, optimized for high performance and scalability, making it suitable for applications such as image search and similarity search."}]}}