--- title: "vald vs vearch" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/vdaas-vald-vs-vearch-vearch" tools: ["vdaas-vald", "vearch-vearch"] --- # vald vs vearch *GraphCanon updated Sep 20, 2026* ## Verdict Pick vald if 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; pick vearch if vearch is a distributed vector search engine for AI-native applications, supporting cloud-native deployment and retrieval-augmented generation. [vald](https://vald.vdaas.org) reports 1.7k GitHub stars, 95 forks, and 147 open issues, last pushed Sep 16, 2026. [vearch](https://vearch.github.io) has 2.3k stars, 365 forks, and 170 open issues, last pushed Jul 27, 2026. Figures are from public GitHub metadata via [vald's repository](https://github.com/vdaas/vald) and [vearch's repository](https://github.com/vearch/vearch). | | [vald](/tools/vdaas-vald.md) | [vearch](/tools/vearch-vearch.md) | | --- | --- | --- | | Tagline | A Highly Scalable Distributed Vector Search Engine | Distributed vector search for AI-native applications | | Stars | 1,728 | 2,326 | | Forks | 95 | 365 | | Open issues | 147 | 170 | | Language | Go | Python | | Adopt for | 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. | Vearch is a distributed vector search engine for AI-native applications, supporting cloud-native deployment and retrieval-augmented generation. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Vearch is available under the Apache License, Version 2.0, allowing for free use, modification, and distribution. | | Categories | Data & Retrieval, Vector Databases | Data & Retrieval, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [vald](/tools/vdaas-vald.md) | [vearch](/tools/vearch-vearch.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 2d | 53d | | Open issues (now) | 147 | 170 | | Stars delta | +14 (30d) | +9 (30d) | | Full report | [trust report](/tools/vdaas-vald/trust.md) | [trust report](/tools/vearch-vearch/trust.md) | ## Decision facts: vald - **Requirements:** Requires Kubernetes 1.19 or newer.; Hardware must support AVX2 instructions for optimal performance. - **Adopt for:** 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. ## Decision facts: vearch - **Pricing:** freemium - Vearch is free and open-source under the Apache License, Version 2.0, with no additional costs for the core software. - **Requirements:** Min 2 GB RAM; Vearch supports Kubernetes deployment, which requires a Kubernetes cluster. - **Adopt for:** Vearch is a distributed vector search engine for AI-native applications, supporting cloud-native deployment and retrieval-augmented generation. - **License detail:** Vearch is available under the Apache License, Version 2.0, allowing for free use, modification, and distribution. ## Choose when ### Choose vald if… - vald is primarily Go; vearch is Python. - Requirements: Requires Kubernetes 1.19 or newer.; Hardware must support AVX2 instructions for optimal performance.. - Tags unique to vald: anng, approximate-nearest-neighbor-search, distributed-systems, golang. - When you need a scalable solution for high-dimensional data search, Vald can handle large volumes of data efficiently. ### Choose vearch if… - vearch is primarily Python; vald is Go. - Pricing: Vearch is free and open-source under the Apache License, Version 2.0, with no additional costs for the core software.. - Requirements: Min 2 GB RAM; Vearch supports Kubernetes deployment, which requires a Kubernetes cluster.. - Tags unique to vearch: ai-native, document-retrieval, embeddings, hybrid-search. - When you need a cloud-native deployment option for vector search, as Vearch supports Kubernetes deployment out-of-the-box. ## When NOT to use vald - 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. ## When NOT to use vearch - If your project does not require cloud-native deployment or Kubernetes integration, Vearch might offer more features than necessary. - If your application does not benefit from retrieval-augmented generation, Vearch's specialized features might not be fully utilized. - For scenarios where the application does not involve AI-native operations, Vearch's specialized design for AI-native applications might not be the best fit. ## Common questions ### What is the difference between vald and vearch? vald: A Highly Scalable Distributed Vector Search Engine. vearch: Distributed vector search for AI-native applications. See the comparison table for live GitHub stats and shared categories. ### When should I choose vald over vearch? Choose vald over vearch when vald is primarily Go; vearch is Python; Requirements: Requires Kubernetes 1.19 or newer.; Hardware must support AVX2 instructions for optimal performance.; Tags unique to vald: anng, approximate-nearest-neighbor-search, distributed-systems, golang; When you need a scalable solution for high-dimensional data search, Vald can handle large volumes of data efficiently. ### When should I choose vearch over vald? Choose vearch over vald when vearch is primarily Python; vald is Go; Pricing: Vearch is free and open-source under the Apache License, Version 2.0, with no additional costs for the core software.; Requirements: Min 2 GB RAM; Vearch supports Kubernetes deployment, which requires a Kubernetes cluster.; Tags unique to vearch: ai-native, document-retrieval, embeddings, hybrid-search; When you need a cloud-native deployment option for vector search, as Vearch supports Kubernetes deployment out-of-the-box. ### When should I avoid vald? 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. ### When should I avoid vearch? If your project does not require cloud-native deployment or Kubernetes integration, Vearch might offer more features than necessary. If your application does not benefit from retrieval-augmented generation, Vearch's specialized features might not be fully utilized. For scenarios where the application does not involve AI-native operations, Vearch's specialized design for AI-native applications might not be the best fit. ### Is vald or vearch more popular on GitHub? vearch has more GitHub stars (2,326 vs 1,728). Stars measure visibility, not whether either tool fits your constraints. ### Are vald and vearch open source? Yes - both are open-source projects on GitHub (vald: Apache-2.0, vearch: Apache-2.0). ### Where can I find alternatives to vald or vearch? GraphCanon lists graph-backed alternatives at [vald alternatives](/tools/vdaas-vald/alternatives) and [vearch alternatives](/tools/vearch-vearch/alternatives) ([vald markdown twin](/tools/vdaas-vald/alternatives.md), [vearch markdown twin](/tools/vearch-vearch/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/vdaas-vald-vs-vearch-vearch.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, vald or vearch? vald: Very active. vearch: Steady. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for vald and vearch? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [vald trust report](/tools/vdaas-vald/trust); [vearch trust report](/tools/vearch-vearch/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=vdaas-vald`](/api/graphcanon/graph?tool=vdaas-vald) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_