--- title: "aquila vs vald" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/aquila-network-aquila-vs-vdaas-vald" tools: ["aquila-network-aquila", "vdaas-vald"] --- # aquila vs vald *GraphCanon updated Aug 2, 2026* ## Verdict Pick aquila if aquila is an efficient neural search engine designed for indexing latent vectors and JSON metadata while performing k-NN searches; pick vald if vald is written in Go, licensed under Apache-2.0, for highly scalable vector search tasks on Kubernetes. [aquila](https://aquila.network) reports 379 GitHub stars, 26 forks, and 13 open issues, last pushed May 6, 2024. [vald](https://vald.vdaas.org) has 1.7k stars, 95 forks, and 146 open issues, last pushed Aug 2, 2026. Figures are from public GitHub metadata via [aquila's repository](https://github.com/Aquila-Network/aquila) and [vald's repository](https://github.com/vdaas/vald). | | [aquila](/tools/aquila-network-aquila.md) | [vald](/tools/vdaas-vald.md) | | --- | --- | --- | | Tagline | Efficient Neural Search Engine | A Highly Scalable Distributed Vector Search Engine | | Stars | 379 | 1,714 | | Forks | 26 | 95 | | Open issues | 13 | 146 | | Language | HTML | Go | | Adopt for | Aquila is an efficient neural search engine designed for indexing latent vectors and JSON metadata while performing k-NN searches. | Vald is written in Go, licensed under Apache-2.0, for highly scalable vector search tasks on Kubernetes. | | Persona | - | - | | Runtime | - | - | | License | - | Apache-2.0 | | Categories | Data & Retrieval, Vector Databases | Data & Retrieval, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [aquila](/tools/aquila-network-aquila.md) | [vald](/tools/vdaas-vald.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 817d | 0d | | Open issues (now) | 13 | 146 | | Full report | [trust report](/tools/aquila-network-aquila/trust.md) | [trust report](/tools/vdaas-vald/trust.md) | ## Decision facts: aquila - **Adopt for:** Aquila is an efficient neural search engine designed for indexing latent vectors and JSON metadata while performing k-NN searches. ## Decision facts: vald - **Adopt for:** Vald is written in Go, licensed under Apache-2.0, for highly scalable vector search tasks on Kubernetes. ## Choose when ### Choose aquila if… - aquila is primarily HTML; vald is Go. - Tags unique to aquila: embedding, faiss, feature-vectors, image-search. - When deploying a solution that requires the processing of feature vectors in image or video search contexts, where efficiency in approximate nearest neighbor search is necessary ### Choose vald if… - vald is primarily Go; aquila is HTML. - Tags unique to vald: anng, cloud-native, distributed-systems, high-dimensional-data. - Requires high-performance searches in a distributed system ## When NOT to use aquila - If the development team lacks experience with Docker, as Aquila's setup heavily relies on Docker images to run locally or in a big data configuration - In scenarios where strict control over metadata and vector indexing is required beyond what JSON and latent vectors can provide ## When NOT to use vald - Need lower scalability vector search solutions - Cannot use Kubernetes 1.19 or above - Do not have AVX2 support in the system environment ## Common questions ### What is the difference between aquila and vald? aquila: Efficient Neural Search Engine. vald: A Highly Scalable Distributed Vector Search Engine. See the comparison table for live GitHub stats and shared categories. ### When should I choose aquila over vald? Choose aquila over vald when aquila is primarily HTML; vald is Go; Tags unique to aquila: embedding, faiss, feature-vectors, image-search; When deploying a solution that requires the processing of feature vectors in image or video search contexts, where efficiency in approximate nearest neighbor search is necessary. ### When should I choose vald over aquila? Choose vald over aquila when vald is primarily Go; aquila is HTML; Tags unique to vald: anng, cloud-native, distributed-systems, high-dimensional-data; Requires high-performance searches in a distributed system. ### When should I avoid aquila? If the development team lacks experience with Docker, as Aquila's setup heavily relies on Docker images to run locally or in a big data configuration In scenarios where strict control over metadata and vector indexing is required beyond what JSON and latent vectors can provide ### When should I avoid vald? Need lower scalability vector search solutions Cannot use Kubernetes 1.19 or above Do not have AVX2 support in the system environment ### Is aquila or vald more popular on GitHub? vald has more GitHub stars (1,714 vs 379). Stars measure visibility, not whether either tool fits your constraints. ### Are aquila and vald open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to aquila or vald? GraphCanon lists graph-backed alternatives at [aquila alternatives](/tools/aquila-network-aquila/alternatives) and [vald alternatives](/tools/vdaas-vald/alternatives) ([aquila markdown twin](/tools/aquila-network-aquila/alternatives.md), [vald markdown twin](/tools/vdaas-vald/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/aquila-network-aquila-vs-vdaas-vald.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, aquila or vald? aquila: Dormant. vald: Very active. 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 aquila and vald? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [aquila trust report](/tools/aquila-network-aquila/trust); [vald trust report](/tools/vdaas-vald/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=aquila-network-aquila`](/api/graphcanon/graph?tool=aquila-network-aquila) - 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/_